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Microtubules originate asymmetrically at the somatic golgi and are guided via Kinesin2 to maintain polarity within neurons

  1. Amrita Mukherjee
  2. Paul S Brooks
  3. Fred Bernard
  4. Antoine Guichet
  5. Paul T Conduit  Is a corresponding author
  1. Department of Zoology, University of Cambridge, United Kingdom
  2. Université de Paris, CNRS, Institut Jacques Monod, France
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Cite this article as: eLife 2020;9:e58943 doi: 10.7554/eLife.58943

Abstract

Neurons contain polarised microtubule arrays essential for neuronal function. How microtubule nucleation and polarity are regulated within neurons remains unclear. We show that γ-tubulin localises asymmetrically to the somatic Golgi within Drosophila neurons. Microtubules originate from the Golgi with an initial growth preference towards the axon. Their growing plus ends also turn towards and into the axon, adding to the plus-end-out microtubule pool. Any plus ends that reach a dendrite, however, do not readily enter, maintaining minus-end-out polarity. Both turning towards the axon and exclusion from dendrites depend on Kinesin-2, a plus-end-associated motor that guides growing plus ends along adjacent microtubules. We propose that Kinesin-2 engages with a polarised microtubule network within the soma to guide growing microtubules towards the axon; while at dendrite entry sites engagement with microtubules of opposite polarity generates a backward stalling force that prevents entry into dendrites and thus maintains minus-end-out polarity within proximal dendrites.

Introduction

Microtubules are polarised α/β-tubulin-based polymers essential for cell viability, providing pushing and pulling forces, structural support or tracks for the transport of intracellular cargo (Goodson and Jonasson, 2018). α-tubulin is located at the so-called minus end and β-tubulin is exposed at the so-called plus end, which is typically more dynamic. This inherent microtubule polarity is important for cell polarity, as different motor proteins (Kinesins and Dynein) move cargo along microtubules in a specific direction – Dynein towards the minus end and most Kinesins towards the plus end. In neurons, most plus ends point away from the soma in axons (plus-end-out microtubules), while the microtubules in dendrites are either of mixed polarity or are predominantly minus-end-out (Hill et al., 2012; Kapitein and Hoogenraad, 2015; Kelliher et al., 2019; Tas et al., 2017). This difference between axons and dendrites is important for the correct distribution of cargo throughout the neuron (Harterink et al., 2018; Kapitein and Hoogenraad, 2015; Tas et al., 2017).

Within cells de novo assembly of new microtubules, that is microtubule nucleation, is kinetically unfavourable and is templated and catalysed by multi-protein γ-tubulin ring complexes (γ-TuRCs) (Tovey and Conduit, 2018). Knockdown of γ-TuRCs within model systems affects dynamic microtubules in all neuronal compartments (Nguyen et al., 2014; Ori-McKenney et al., 2012; Sánchez-Huertas et al., 2016; Yamada and Hayashi, 2019; Yau et al., 2014) and mutations in γ-TuRC genes have been linked to human neurodevelopmental disorders (Bahi-Buisson et al., 2014; Mitani et al., 2019; Poirier et al., 2013). γ-TuRCs are typically inactive until they are recruited to specific sites within cells, such as microtubule organising centres (MTOCs), the cytosol around mitotic chromatin, or the sides of pre-existing microtubules via binding to Augmin/HAUS complexes (Farache et al., 2018; Lin et al., 2015; Meunier and Vernos, 2016; Sanchez and Feldman, 2017; Teixido-Travesa et al., 2012). A range of MTOCs exist, including centrosomes, the Golgi apparatus and the nuclear envelope, and different cells use different MTOCs to help generate and organise their specific microtubule arrays (Sanchez and Feldman, 2017). γ-TuRC recruitment occurs via γ-TuRC ‘tethering proteins’, such as Drosophila Centrosomin (Cnn), that simultaneously bind to the γ-TuRC and a particular MTOC, and can also help activate the γ-TuRC (Tovey and Conduit, 2018).

Although γ-tubulin is important within neurons (Nguyen et al., 2014; Ori-McKenney et al., 2012; Sánchez-Huertas et al., 2016; Yamada and Hayashi, 2019; Yau et al., 2014), it remains unclear how microtubule nucleation is regulated. During early development of mammalian neurons, the centrosome within the soma nucleates microtubules (Stiess et al., 2010) that are severed and transported into neurites via motor-based microtubule sliding (Baas et al., 2005). Microtubule sliding is also important for axon outgrowth in Drosophila cultured neurons (Del Castillo et al., 2015; Lu et al., 2013), and for establishing microtubule polarity (del Castillo et al., 2015; Klinman et al., 2017; Rao et al., 2017; Yan et al., 2013; Zheng et al., 2008). Centrosomes are inactivated, however, at later developmental stages (Stiess et al., 2010) and are dispensable for neuronal development in both mammalian and fly neurons (Nguyen et al., 2011; Stiess et al., 2010). No other active MTOCs within the neuronal soma have been described. Nevertheless, microtubules continue to grow within the soma (Nguyen et al., 2011; Sánchez-Huertas et al., 2016), and in mammalian neurons this depends in part on the HAUS complex (Sánchez-Huertas et al., 2016), which is also important for microtubule growth within axons and dendrites (Cunha-Ferreira et al., 2018; Sánchez-Huertas et al., 2016). Some MTOCs have been identified within dendrites: the basal body, or its surrounding region, within the distal part of C. elegans ciliated neurons acts as an MTOC, as does a similar region within the URX non-ciliated neuron (Harterink et al., 2018); an MTOC made from endosomes that tracks the dendritic growth cone in C. elegans PVD neurons has recently been identified (Liang et al., 2020); and fragments of Golgi called Golgi outposts within the dendrites of Drosophila dendritic arborisation (da) neurons are thought to recruit γ-TuRCs and act as MTOCs (Ori-McKenney et al., 2012; Yalgin et al., 2015; Zhou et al., 2014).

Drosophila larval da neurons are a popular in vivo neuronal model (Jan and Jan, 2010). Ease of imaging and genetic manipulation coupled with the ability to examine different neuronal classes, each with a stereotypical dendritic branching pattern, make them a model of choice when examining microtubule organisation within neurons. Four classes exist, including class I neurons that are proprioceptive and have the simplest ‘comb-like’ dendritic branching pattern, and class IV neurons that are nociceptive and have the most elaborate branching pattern, tiling the surface of the larva (Figure 1—figure supplement 1; Grueber et al., 2002). In both neuronal classes, microtubules in axons are predominantly plus-end-out throughout development, but microtubule polarity in dendrites progressively becomes more minus-end-out as the neurons develop; at two days post larval hatching the majority of dynamic microtubules are minus-end-out (Hill et al., 2012; Stone et al., 2008). Microtubule polarity within da neurons can be disrupted when microtubule regulators are depleted (Mattie et al., 2010; Nguyen et al., 2014; Ori-McKenney et al., 2012; Rolls and Jegla, 2015; Sears and Broihier, 2016; Weiner et al., 2016; Yalgin et al., 2015; Zhou et al., 2014), but we lack a full understanding of how microtubule polarity is established and maintained.

Golgi outposts are thought to provide localised sites of microtubule nucleation within the dendrites of da neurons to help regulate dendritic outgrowth and microtubule polarity (Ori-McKenney et al., 2012; Yalgin et al., 2015; Zhou et al., 2014). Unlike the somatic Golgi, which comprises cis, medial, and trans compartments organised into stacks and ribbons (Kondylis and Rabouille, 2009; Nakamura et al., 1995), Golgi outposts can be either single- or multi-compartment units with multi-compartment units having a higher propensity to initiate microtubule growth (Zhou et al., 2014). Within class I da neurons, Golgi outpost-mediated nucleation is thought to be dependent on the γ-TuRC-tethering protein Cnn and to help restrict dendritic branching (Yalgin et al., 2015), while within class IV neurons Golgi outpost-mediated nucleation is believed to be dependent on Pericentrin-like protein (Plp) and to help promote dendritic branching (Ori-McKenney et al., 2012). There remains some uncertainty, however, about the role of Golgi outposts in microtubule nucleation, as a separate study that examined the localisation of ectopically expressed γ-tubulin-GFP concluded that γ-tubulin localises predominantly to dendritic branch points in a Golgi outpost-independent manner (Nguyen et al., 2014).

In this study, we initially aimed to identify sites of microtubule nucleation within Drosophila da neurons. We used endogenously tagged γ-tubulin-GFP as a proxy for γ-TuRCs and performed a detailed analysis of γ-tubulin localisation within both class I and class IV da neurons. We find variation between neuronal classes in how γ-tubulin localises within dendrites, but find that the most prominent localisation of γ-tubulin is at the cis-compartment of somatic Golgi stacks within all sensory neurons of the dorsal cluster. This asymmetric γ-tubulin-Golgi association is not dependent on either Cnn or Plp, suggesting another molecule must regulate γ-TuRC recruitment to the Golgi. Tracking of EB1-GFP comets within the soma suggests that microtubules are nucleated asymmetrically from the somatic Golgi. We find that these Golgi-derived microtubules initially grow preferentially towards the axon. During growth, they are also guided towards the axon and away from dendrites in a Kinesin-2-dependent manner, and they readily enter the axon contributing to plus-end-out microtubule polarity. In contrast, the relatively small number of microtubules that do grow towards a dendrite are normally excluded and this also depends upon Kinesin-2. After Kinesin-2 depletion, growing microtubules more readily approach and enter the dendrites causing a dramatic increase in the proportion of anterograde microtubules in proximal dendrites. This results in a reversal of overall microtubule polarity in proximal dendrites from predominantly minus-end-out to predominantly plus-end-out. We therefore propose that plus-end-associated Kinesin-2 guides growing microtubules towards the axon and away from dendrites along a polarised microtubule network within the soma, while at dendrite entry points Kinesin-2 generates a stalling force on growing microtubules when engaging dendritic microtubules of opposite polarity.

Results

A detailed analysis of endogenous γ-tubulin localisation within class I and class IV da neurons

We began by examining the localisation of γ-tubulin (as a proxy for γ-TuRCs) within class I and class IV da neurons. To avoid any potential artefacts induced by ectopic overexpression, we used alleles where γ-tubulin23C (the zygotic form of γ-tubulin) was tagged at its endogenous locus with GFP (Tovey and Conduit, 2018 and this study). We generated fly stocks expressing two genetic copies of endogenously-tagged γ-tubulin23C-GFP (hereafter γ-tubulin-GFP) and the membrane marker mCD8-RFP, expressed either in class I or class IV da neurons, and imaged living animals. The most striking and obvious localisation of γ-tubulin-GFP was as multiple bright and relatively large puncta within the soma of both neuronal types (Figure 1A; Figure 2A); we address this localisation in subsequent sections. We could also detect discrete accumulations of γ-tubulin-GFP at specific dendritic sites (Figure 1A; Figure 2A), which were typically dim and varied between class I and class IV neurons. We therefore describe the localisation of γ-tubulin-GFP within dendrites for each neuron type in turn below.

Figure 1 with 2 supplements see all
Endogenously-tagged γ-tubulin-GFP localises to a fraction of branchpoints and dendritic bubbles within class I da neurons.

(A) Fluorescent confocal images of the proximal region of a class I da neuron expressing mCD8-RFP (greyscale) within a living 3rd instar larva expressing endogenously-tagged γ-tubulin-GFP (green). Left panel (A) shows an overlay of the GFP and RFP signals, right panel (A’) shows only the GFP signal with the outline of the neuron drawn for clarity; white, blue and orange arrowheads indicate γ-tubulin-GFP puncta/accumulations within dendritic stretches, branchpoints, and dendritic bubbles, respectively. (B,C) Selected images of γ-tubulin-GFP-positive branchpoints (B) or dendritic bubbles (C) from living neurons as in (A). Individual mCD8-RFP channel images (greyscale) have been included for clarity. (D–F) Confocal images show branchpoints (D,E) or dendritic bubbles (F) from 3rd instar larvae expressing endogenous γ-tubulin-GFP fixed and immunostained for GFP (green), GM130 (magenta) and HRP (greyscale). γ-tubulin-GFP signal was rarely observed co-localising with GM130 and HRP signal (D), and frequently observed independent of the Golgi markers at both branchpoints (E) and dendritic bubbles (F).

Endogenously-tagged γ-tubulin-GFP localises to a small fraction of proximal Golgi outposts within class IV da neurons.

(A) Fluorescent confocal images of the proximal region of a class IV da neuron expressing UAS-mCD8-RFP (greyscale) within a living 3rd instar larva expressing endogenously-tagged γ-tubulin-GFP (green). Left panel (A) shows an overlay of the GFP and RFP signals, right panel (A’) shows only the GFP signal with the outline of the neuron drawn for clarity; insets show examples of distal dendrites located >200 μm from the soma; white and yellow arrowheads indicate bright or weak γ-tubulin-GFP puncta, respectively, within proximal or distal dendrites. (B) Images show a γ-tubulin-GFP-positive proximal branchpoint from a 3rd instar larva expressing endogenous γ-tubulin-GFP fixed and immunostained for GFP (green), GM130 (magenta) and HRP (greyscale). Asterisks indicate GM130 foci from overlapping epidermal cells. Arrowhead indicates an example of a γ-tubulin-GFP-positive Golgi outpost observed within proximal class IV branchpoints. (C) Confocal images show the proximal region of a class IV dendritic arbor within a 3rd instar larva expressing ManII-GFP (to mark medial Golgi) fixed and immunostained for GFP (fire) and HRP (greyscale within insets). Insets show HRP staining alone.

For class I da neurons we focussed on the ddaE neuron (hereafter class I neurons), as these have been the most widely characterised. From 13 class I neurons analysed, we detected an average of 1.1 discrete γ-tubulin-GFP puncta per 100 μm of dendrite (Figure 1A). Most puncta were just above background intensity levels, although some were bright, and they were found more frequently away from branchpoints (80.2% of puncta) than within branchpoints (19.8% of puncta). We could detect γ-tubulin-GFP signal in 18% of branchpoints; in approximately half of these branchpoints the γ-tubulin-GFP appeared as puncta, often with multiple puncta per branchpoint, while in the other half of branchpoints the γ-tubulin-GFP signal was spread more diffusely through the branchpoint (Figure 1B). This diffuse signal was similar to that observed when γ-tubulin-GFP is overexpressed (Nguyen et al., 2014; Weiner et al., 2020; Figure 1—figure supplement 2A), although it appeared that the frequency of branchpoint occupancy and the strength of the endogenous γ-tubulin-GFP signal was lower than that observed with ectopically expressed UAS-γ-tubulin-GFP. It is possible that the localisation of endogenous γ-tubulin-GFP at branchpoints represents the recently reported recruitment of γ-tubulin to endosomes at branchpoints that provide a platform for microtubule nucleation (Weiner et al., 2020). We have not tested here, however, whether the diffuse or punctate γ-tubulin-GFP signals, or both, are functionally important at branchpoints.

We noticed that class I neurons display ‘bubbles’, where the diameter of the dendrite is locally increased to differing extents (Figure 1A); there were on average 2.6 ‘bubbles’ per 100 μm of dendrite with a larger fraction found further from the soma;~16.5% of bubbles contained γ-tubulin-GFP signal, either as weak puncta or a diffuse signal (Figure 1C), and ~36.7% of the γ-tubulin-GFP puncta that we observed within dendrites were found within bubbles. It remains to be tested whether the accumulation of γ-tubulin within these bubbles is functionally relevant.

To test whether γ-tubulin-GFP puncta within class I dendrites associate with Golgi outposts, we fixed and stained larval preparations expressing γ-tubulin-GFP with antibodies against HRP, which stain neuronal membranes, GFP, and the Golgi protein GM130. Out of 9 neurons from three larvae, we could only find one example where γ-tubulin-GFP colocalised with an HRP punctum, and in this case GM130 was also colocalised suggesting it was a Golgi outpost (Figure 1D). GM130 labels only multi-compartment Golgi outposts (Zhou et al., 2014) but HRP probably labels most, if not all, Golgi outposts. We chose not to use the ectopically expressed Golgi marker UAS-ManII-GFP used in some previous studies, as this has been reported to ‘leak’ into endosomes within the dendrites of class I da neurons (Weiner et al., 2020). Consistent with this, we found that 221-Gal4-driven UAS-ManII-GFP can form puncta, enrichments, and long stretches within class I dendrites that are not associated with HRP staining (Figure 1—figure supplement 2B). These apparent cytosolic accumulations may therefore be due to an excess of ManII protein within the dendrites. This appeared to be specific to dendrites, however, as UAS-ManII-GFP always colocalised with HRP staining within the soma (Figure 1—figure supplement 2C), possibly due to the higher concentration of Golgi within the soma. All dendritic γ-tubulin-GFP puncta (except for the single occasion noted above), including those within branchpoints, dendrites and bubbles, did not colocalise with HRP or GM130 staining (Figure 1E,F). Thus, our data strongly suggest that γ-TuRCs do not typically associate with Golgi outposts within class I neurons, and instead localise to a fraction of branchpoints and dendritic bubbles in a Golgi outpost-independent manner.

For class IV neurons we focussed on the ddaC neuron (hereafter class IV neurons), as these have also been the most widely characterised. We analysed two distinct dendritic regions that we term proximal (within ~100 μm of the soma) and distal (over ~200 μm from the soma). We detected an average of 2.3 and 0.3 γ-tubulin-GFP puncta per 100 μm of dendrite within proximal (10 neurons analysed) and distal (seven neurons analysed) regions, respectively, and the intensity of the majority was only just above background levels, including all of the puncta in the distal regions (Figure 2A). Nevertheless, we consistently observed bright γ-tubulin-GFP puncta within the primary and secondary branchpoints close to the soma (Figure 2A). 44.6% of γ-tubulin-GFP puncta observed in the proximal regions were found within the large primary and secondary branchpoints, and 57% of these branchpoints contained γ-tubulin-GFP puncta, which were always bright relative to other foci within the dendrites (Figure 2A). Staining with HRP and GM130 antibodies showed that these bright γ-tubulin-GFP puncta associated with Golgi outposts (Figure 2B). Intriguingly, γ-tubulin-GFP only colocalised with HRP puncta that also associated with GM130 (Figure 2B), suggesting that γ-TuRCs are recruited only to multi-compartment Golgi outposts. The high frequency of proximal branchpoints that contained γ-tubulin-GFP puncta contrasted with the near absence of γ-tubulin-GFP puncta within the smaller branchpoints of the distal arbor, where only 1.7% of branchpoints contained detectable but very weak γ-tubulin-GFP signal (Figure 2A insets).

In contrast to class I neurons, we found that the vast majority of ectopically expressed (via ppk-Gal4) ManII-GFP puncta within class IV neurons colocalised with HRP and did not form large accumulations or stretches within the dendrites (Figure 2C), suggesting that ectopically expressed ManII-GFP can be used as a reliable marker of Golgi outposts in class IV neurons. We observed an average of ~12 and~5 ManII-GFP-positive Golgi outposts within proximal and distal regions, respectively, which is consistent with previous observations (Zheng et al., 2008) and far higher than the 2.3 and 0.3 γ-tubulin-GFP puncta per 100 μm that we observed in proximal and distal dendrites (compare Figure 2A to Figure 2C). Thus, only Golgi outposts within the proximal branchpoints of class IV neurons associate readily with γ-tubulin. In contrast to class I neurons, we very rarely observed γ-tubulin-GFP spread diffusely through branchpoints, suggesting that Golgi outpost-independent accumulation of γ-tubulin at branchpoints is specific to class I neurons. Moreover, we found far fewer dendritic bubbles per 100 μm of dendrite in class IV neurons (0.4 and 0.8 per 100 μm dendrite in proximal and distal regions, respectively). Collectively, our data show that Golgi outposts within class IV neuron branchpoints close to the soma frequently associate with γ-tubulin, but that the majority of Golgi outposts do not. Whether this proximal Golgi outpost associated γ-tubulin represents fully functional γ-TuRCs remains to be tested.

γ-tubulin-GFP localises to the somatic Golgi of sensory neurons in a Cnn- and Plp-independent manner

The most striking and obvious localisation of γ-tubulin-GFP within both class I and class IV neurons was as multiple large bright puncta within their soma (see images of neurons from live animals in Figure 1A and Figure 2A, and of fixed and stained neurons in Figure 3A–C). We also observed similar puncta within the somas of other nearby sensory neurons (Figure 3A), including external sensory (es) neurons; these sensory neurons possess basal bodies that appear to associate with large amounts of γ-tubulin-GFP (Figure 3A). Staining with antibodies against HRP and the Golgi marker GM130 showed that all γ-tubulin-GFP puncta within the soma of all sensory neurons associated with somatic Golgi stacks (Figure 3B,C; Figure 3—figure supplement 1), which are typically scattered throughout the cytosol in Drosophila cells while still maintaining cis-medial-trans polarity (Kondylis and Rabouille, 2009). These Golgi stacks can be oriented side-on or face-on to the imaging plane, appearing either more elongated or circular, respectively. Our staining showed that the signals of γ-tubulin-GFP and GM130 partially overlapped at side-on stacks, with γ-tubulin-GFP extending further out laterally than GM130 (Figure 3B; Figure 3—figure supplement 1A); γ-tubulin-GFP surrounded GM130 in a ring-like pattern on face-on stacks (Figure 3C; Figure 3—figure supplement 1B). To determine whether γ-tubulin associates specifically with the cis-Golgi, as has been suggested for γ-tubulin in non-neuronal mammalian cells (Wu et al., 2016), we stained the neurons with antibodies against HRP, GM130, and Arl1. The mammalian homologue of GM130 is a cis-Golgi protein, while Arl1 is a known trans Golgi protein in Drosophila (Munro, 2011). We found that the GM130 and Arl1 signals were offset at side-on stacks, consistent with them being cis- and trans-Golgi proteins, respectively. Moreover, γ-tubulin colocalised with GM130 rather than Arl1 (Figure 3D). Together, this shows that γ-tubulin-GFP, possibly in the form of γ-TuRCs, localises to the rims of the cis-Golgi stack in the soma of Drosophila da neurons.

Figure 3 with 1 supplement see all
Endogenously-tagged γ-tubulin-GFP localises to the somatic Golgi of sensory neurons.

(A) Confocal images show the somas and some proximal dendrites of sensory neurons within the dorsal cluster: class I (yellow), class IV (blue), as (pink) and other (orange) from a 3rd instar larva expressing endogenously-tagged γ-tubulin-GFP and immunostained for GFP (green) and HRP (marking Golgi stacks, greyscale). Upper panel (A) shows an overlay of the GFP and HRP signals, lower panel (A’) shows only the GFP signal with coloured neuronal outlines drawn for clarity. (B, C) Confocal images show the somas of class I (B) or class IV (C) da neurons from a 3rd instar larva expressing endogenously-tagged γ-tubulin-GFP fixed and immunostained for GFP (green), GM130 (magenta) and HRP (greyscale). Enlarged boxes in (B) and (C) show side-on and face-on stacks, respectively. (D) Confocal images show an example of a single Golgi stack within a da neuron from a 3rd instar larva expressing endogenously-tagged γ-tubulin-GFP fixed and immunostained for GFP (green), Arl1 (trans-Golgi, magenta) and GM130 (cis-Golgi, greyscale). The larva was also stained with HRP antibodies to identify neurons, but this channel has been omitted for clarity.

Two proteins, Cnn and Plp, were possible candidates for γ-TuRC recruitment to the somatic Golgi, as their homologues are required for proper organisation of microtubules at the somatic Golgi in cycling mammalian cells (Rios, 2014; Roubin et al., 2013; Wang et al., 2010; Wu et al., 2016), and Cnn and Plp have been implicated in γ-TuRC recruitment to Golgi outposts in Drosophila class I neurons (Yalgin et al., 2015), with Plp also being implicated in class IV neurons (Ori-McKenney et al., 2012). Cnn is a multi-isoform gene with three sets of isoforms driven by three different promoters (Eisman et al., 2009; Figure 4—figure supplement 1A). Promoter one drives the most-studied isoform (that we term Cnn-P1) that localises to centrosomes during mitosis; promoter two drives isoforms (Cnn-P2) that are yet to be characterised; and promoter three drives isoforms that are expressed specifically within testes (Chen et al., 2017) and so have not been considered in this study. Immunostaining with antibodies against Cnn revealed very weak, if any, signal within the soma or dendrites of the dorsal sensory neurons; while the presumptive basal bodies of the es neurons displayed a strong Cnn signal (data not shown). Given that antibody staining can be problematic, we generated flies where Cnn-P1 or Cnn-P2 were tagged with GFP at their isoform-specific N-termini (hereafter, GFP-Cnn-P1 and GFP-Cnn-P2; Figure 4—figure supplement 1A). The GFP insertions appear functional as flies could be kept as homozygous stocks and the localisation of GFP-Cnn-P1 to centrosomes in syncytial embryos was normal (Figure 4—Video 1). GFP-Cnn-P1 signal was very weak and inconsistent within the soma of living class I da neurons (Figure 4A). In contrast, we could readily detect clear GFP-Cnn-P1 puncta within distal dendritic bubbles in live animals (Figure 4B). In fixed samples, there was a weak GFP-Cnn-P1 signal associated with the somatic Golgi in the dorsal cluster of sensory neurons, similar to that observed in live samples (Figure 4—figure supplement 1B), although we did not detect GFP-Cnn-P1 associated with HRP puncta within dendrites (Figure 4—figure supplement 1B; data not shown). We found a strong GFP-Cnn-P1 signal at the presumptive basal bodies of the es neurons (Figure 4—figure supplement 1B). Collectively our data suggest that GFP-Cnn-P1 does not readily associate with Golgi, but accumulates within a fraction of dendritic bubbles in class I neurons, possibly together with γ-tubulin.

Figure 4 with 2 supplements see all
Cnn-P1 is dispensable for γ-tubulin-GFP recruitment to the somatic Golgi.

(A,B) Fluorescent confocal images of proximal (A) and distal (B) regions of class I da neurons expressing mCD8-RFP (greyscale) within a living 3rd instar larva expressing endogenously-tagged GFP-Cnn-P1 (green). Upper panels show an overlay of the GFP and RFP channels, lower panels show only the GFP channel with the outline of the neurons drawn for clarity. Arrowhead in (A) indicates a rare dendritic GFP-Cnn-P1 puncta within a proximal dendritic bubble, while arrowheads in (B) indicate more frequent GFP-Cnn-P1 accumulations within distal dendritic bubbles. (C) Confocal images show the somas and some proximal dendrites of sensory neurons within the dorsal cluster from a 3rd instar cnn mutant larva expressing endogenously-tagged γ-tubulin-GFP and immunostained for GFP (green), HRP (greyscale) and Cnn (magenta). Images in (C’) and (C’’) show the separate channels for the class I soma and the presumptive basal body of an es neuron, respectively.

In contrast to GFP-Cnn-P1, we did not detect any obvious GFP-Cnn-P2 signal within the soma or dendrites of da neurons in living larvae (Figure 4—figure supplement 1C). Instead, GFP-Cnn-P2 appeared to be expressed within glial cells that ensheath the axons, soma, and part of the proximal dendritic region of the da neurons (Figure 4—figure supplement 1C). These glia are known to help regulate dendritic development (Han et al., 2011; Sepp and Auld, 2003; Yadav et al., 2019), and thus Cnn-P2 isoforms may have an indirect role in dendritic arbor growth. GFP-Cnn-P2 also localised strongly to the presumptive basal body of es neurons (data not shown). Consistent with the localisation pattern of GFP-Cnn-P1 and GFP-Cnn-P2, γ-tubulin-GFP could still associate with the somatic Golgi of the sensory neurons in cnn mutant larvae, but not to the basal bodies of es neurons (Figure 4C). We therefore conclude that Cnn is dispensable for γ-TuRC recruitment to the somatic Golgi within sensory neurons.

In contrast to Cnn, antibodies against Plp readily stained the somatic Golgi in all sensory neurons, including class I and class IV da neurons (Figure 5—figure supplement 1A). The Plp signal was, however, offset from the γ-tubulin-GFP signal at Golgi stacks in both class I and class IV da neurons (Figure 5A,B), suggesting that they localise to different Golgi compartments. Plp also associated with the class IV proximal Golgi outposts (Figure 5C) and the presumptive basal bodies of the es neurons (Figure 5—figure supplement 1B), and was enriched within a fraction of the distal class I dendritic bubbles (Figure 5—figure supplement 1C). Strikingly, γ-tubulin-GFP localisation at the somatic Golgi of all sensory neurons, including class I and class IV neurons was unaffected in plp mutant larvae (Figure 5D). This was also true of the γ-tubulin-positive proximal Golgi outposts in class IV neurons (Figure 5D). The absence of Plp did, however, lead to the loss of γ-tubulin-GFP from the basal bodies of es neurons (Figure 5D). In summary, neither Plp nor Cnn are required for the efficient recruitment of γ-tubulin to the somatic Golgi within sensory neurons, or to the few γ-tubulin-GFP-positive Golgi outposts within the proximal branch points of class IV da neurons, but both are required for the localisation of γ-tubulin-GFP to the basal body region within es neurons.

Figure 5 with 1 supplement see all
Endogenous Plp localises to Golgi but is dispensable for γ-tubulin-GFP recruitment.

(A–C) Confocal images show the somas of a class I (A) or a class IV (B) neuron and a proximal branchpoint of a class IV neuron (C) from 3rd instar larvae expressing γ-tubulin-GFP fixed and immunostained for GFP (green), Plp (magenta) and HRP (greyscale). Arrowhead in (C) indicates a γ-tubulin-GFP-positive Golgi outpost that contains Plp. (D) Confocal images show the somas and some proximal dendrites of sensory neurons within the dorsal cluster: class I (yellow), class IV (blue), es (pink) and other (orange), from a plp mutant 3rd instar larva expressing endogenously-tagged γ-tubulin-GFP and immunostained for GFP (green), HRP (greyscale) and GM130 (magenta). Left panel (D) shows an overlay of the GFP and HRP signal, with insets showing overlays for different neurons, as indicated; right panel (D’) shows the GFP channel with coloured outlines of the different neurons drawn for clarity, with insets showing separate channels for a proximal branchpoint.

Growing microtubules originate asymmetrically from the somatic golgi

We next wanted to assess whether the somatic Golgi is an active MTOC. EB1-GFP binds to growing microtubule ends and generates fluorescent ‘comets’, typically representing growing microtubule plus ends. While the origin of these comets can represent either microtubule regrowth after catastrophe or sites of microtubule nucleation, the position of emerging EB1-GFP comets has been routinely used in Drosophila neurons as a proxy for nucleation sites (Nguyen et al., 2014; Ori-McKenney et al., 2012; Weiner et al., 2020; Yalgin et al., 2015; Zhou et al., 2014). It is generally considered that comets repeatedly emerging from the same location are likely to represent nucleation sites (Ori-McKenney et al., 2012; Zhou et al., 2014). We therefore imaged the soma of class I neurons expressing EB1-GFP and the Golgi marker ManII-mCherry and manually tracked each EB1-GFP comet (Figure 6A; Figure 6—Video 1; the circle of each track represents the latest position of the EB1 comet). Comets could be observed originating at both Golgi stacks and non-Golgi sites. They emerged at different Golgi stacks within the same cell, and sequentially from the same Golgi stack, suggestive of nucleation. Intriguingly, many Golgi-derived comets appeared to grow towards the axon. Measuring the initial angle of each comet’s growth relative to the axon entry site (indicated in Figure 6A) showed that there was a strong bias for initial growth towards the axon (163 comets analysed from 59 Golgi stacks from seven neurons, p<0.001), although some comets did grow away from the axon and thus towards dendrites (Figure 6B). While it is possible that the direction of comet growth can be influenced by comets growing into the soma from the dendrites, which will tend to grow towards the axon, we minimised this effect by quantifying only those comets that originate from Golgi stacks. The comets we analysed are therefore more likely to represent true growth events from the Golgi rather than catastrophe and regrowth of microtubules that originated from dendrites.

Figure 6 with 2 supplements see all
Somatic Golgi stacks nucleate microtubules.

(A) Widefield fluorescent images from a movie showing the soma of a class I da neuron expressing EB1-GFP (greyscale) and ManII-mCherry (magenta). Manually assigned multi-colour tracks of EB1-GFP comets were drawn over each image (filled circle = last location of comet). Arrow indicates a Golgi stack from which sequential EB1-GFP comets emerge; dotted lines show an example of an angle measurement of a comet’s initial growth relative to the axon entry point (orange circle). Time in min:s from the start of the movie is shown. (B) Graph shows a frequency distribution of the initial growth angle (before turning) relative to the axon entry site (as indicated in (A)) of EB1-GFP comets that emerged from Golgi stacks. Negative angles were made positive so as not to distinguish between comets growing to the left or right of the axon. 163 comets from 59 Golgi stacks from seven neurons were analysed. (C) Scatter graph shows the position of the normalised resultant comet vectors (see methods) for each of 44 Golgi stacks from seven neurons. Circle position is representative of the average angle from the axon and how similar the angles were (as indicated). Circle size reflects the number of comets analysed per Golgi stack (as indicated below). (D) Graph shows a frequency distribution of the resultant vector lengths for the comet data (blue) and for 3 sets of data produced using randomly generated angles (grey shades). (E) Widefield fluorescent images from a movie showing the soma of class I da neuron expressing UAS-EB1-GFP (greyscale) and UAS-ManII-mCherry (magenta). The sample was subjected to a warm-cool-warm temperature cycle to induce depolymerisation (5°C; blue outline) and then repolymerisation (20 °C; red outline) of dynamic microtubules. Tracks were manually colour coded: green = comets emerging from Golgi stacks; purple = comets emerging from elsewhere. Time in min:s from the 5°C to 20°C transition is shown.

We also noticed that the direction of initial growth of each comet that emerged from the same Golgi stack was similar, irrespective of their angle from the axon. We therefore generated and plotted normalised resultant vectors (final vector position from a (0,0) origin represented by a blue circle) for the comets from each Golgi stack that produced two or more comets (Figure 6C; see Materials and methods). The angle between the positive Y-axis and a line connecting (0,0) and a given circle on the graph is representative of the overall comet angle from the axon; the distance (d) of each circle from (0,0) is representative of the similarity of comet angles (d = 1 if all angles are the same; d = 0 if all angles are evenly distributed). 77% of the circles were in the upper quadrants (Figure 6C; p<0.001), again showing that there was a preference for comets to grow initially towards the axon. Moreover, there was a bias for resultant vector lengths to be large, as compared to randomly generated data (Figure 6D; p<0.001). We conclude that comets from a particular Golgi stack emerge within a small angle with respect to each other and with a directional preference towards the axon. While not definitive, the similarity in the direction of comets emerging repeatedly from the same Golgi stack is indicative of consecutive microtubule nucleation events.

A temperature-based microtubule nucleation assay suggests that microtubules are nucleated from the somatic Golgi in class I da neurons

The origin of EB1-GFP comets is not a perfect proxy for microtubule nucleation, as EB1-GFP comets also appear during the regrowth of partially depolymerised microtubules. We therefore performed a microtubule nucleation assay using a temperature-control device (CherryTemp, Cherry Biotech) to cool samples rapidly to 5°C and then re-heat them to 20°C during continuous imaging of the sample. Cooling typically causes depolymerisation of dynamic microtubules and warming causes their regrowth. Cooling-warming microtubule nucleation assays have previously been performed in various systems, including Drosophila embryos (Hayward et al., 2014), Drosophila S2 cells (Bucciarelli et al., 2009), and in mammalian cells (Torosantucci et al., 2008). While populations of cold-stable microtubules have been identified in mammalian neurons, cold stability is thought to be induced by binding to MAP6 proteins, which are specific to vertebrates (Bosc et al., 2003; Delphin et al., 2012). We therefore expected that cooling would result in the depolymerisation of at least the dynamic microtubules within Drosophila neurons, allowing us to correlate the position of new comet growth with nucleation sites.

During cooling-warming cycles we observed no obvious effect on the distribution of the somatic Golgi stacks (Figure 6E; Figure 6—Video 2), although thermal-fluctuation-induced movement of the glass coverslip made it difficult to follow the first few timepoints after cooling or warming. When the appropriate focal plane was reached shortly after warming, we could observe EB1-GFP comets emerging from the ManII-mCherry-labelled Golgi structures (green-labelled comets, Figure 6E; Figure 6—Video 2), suggestive of Golgi-located microtubule nucleation events. Within 20 s of warming in Figure 6—Video 2, four comets emerged from Golgi structures (green-labelled comets, Figure 6E; Figure 6—Video 2), while two comets emerged away from the Golgi (purple-labelled comets, Figure 6E; Figure 6—Video 2). During the 2 min and 12 s between warming and the end of the movie, a total of 8 comets emerged from the Golgi with a total of five emerging from non-Golgi sites. The initial emergence of non-Golgi comets is not surprising, given that HAUS, the mammalian homologue of Drosophila Augmin that recruits γ-TuRCs to the sides of pre-existing microtubules, is required for microtubule nucleation events within the soma of mammalian neurons in culture (Sánchez-Huertas et al., 2016). It may also be, however, that the non-Golgi comets grew initially from Golgi stacks in a different focal plane or that these comets represented the re-growth of microtubules that were not fully depolymerised. Indeed, while EB1-GFP comets disappeared rapidly on cooling, suggesting that dynamic microtubules quickly lose their GTP-tubulin cap and thus depolymerise, it is possible that a proportion of microtubules within the soma are cold stable and therefore won’t depolymerise. Presumably, most of these stable microtubules would remain stable, but it is possible that some would start to grow and thus contribute to the EB1-GFP comets that we observe on warming.

In our opinion, the best evidence for microtubule nucleation occurring at the somatic Golgi comes from the observation that several comets emerged from Golgi stacks relatively late after warming. For example, in Figure 6—Video 2 four comets emerged from Golgi stacks at least 50 s post warming. While some of these late comets emerged from a Golgi stack that had generated a comet immediately after warming, others emerged from Golgi stacks that had not generated a comet immediately after warming. Most importantly, the direction of all late emerging comets suggests that they were not simply generated by catastrophe-rescue of a microtubule that had grown immediately after warming. While it is impossible to rule out that these late emerging comets could have been generated by re-growing microtubules that were originally out of focus, the data strongly suggests that they instead represent genuine nucleation events from the Golgi .

Growing microtubules within the soma are guided towards the axon while being excluded from entering dendrites in a Kinesin-2-dependent manner

We next wanted to determine the fate of growing microtubules within the soma. We therefore imaged and tracked EB1-GFP comets within the soma and proximal axons and dendrites of 13 class I da neurons (Figure 7A; Figure 7—Video 1). These neurons have at least two primary dendrites but only a single axon; however, comets that initiated within the soma often grew into the axon, while few entered dendrites (Figure 7—Video 1). We found that this was due to two major factors. The first was that a higher proportion of comets reached the axon entry site: of the 666 comets that had initiated within the soma across all movies 104 approached the entrance to the axon (15.6%), while only 47 approached the entrance of a dendrite (7.1%) (Figure 7C; p<0.001); the remaining 77.3% of comets terminated within the soma away from the axon or dendrites. The second important factor was that when comets arrived at either the axon entry site or a dendritic entry site, they had more chance of entering the axon: of the 104 comets that approached the entrance to an axon across all movies 56 entered (53.8%), while of the 47 comets that approached the entrance to a dendrite only 13 entered (27.7%) (Figure 7D; p<0.001). Overall, 8.4% of all comets that originated in the soma entered the axon while only 2.0% entered a dendrite. In summary, growing microtubule plus ends within the soma preferentially reach the entrance to the axon and can readily enter, while the few that reach dendrites are normally excluded from entering.

Figure 7 with 3 supplements see all
Microtubules within the soma grow preferentially towards the axon and are excluded from entering dendrites in a Kinesin-2-dependent manner.

(A,B) Widefield fluorescent images from movies showing the somas of class I da neurons expressing UAS-EB1-GFP and either γ-tubulin-37C RNAi (control) (A) or UAS-Kap3 RNAi (B). Manually assigned multi-colour tracks of EB1-GFP comets are drawn over each image (filled circle = last location of comet). Time in min:s from the start of the movie is shown. (C) Graph shows the % of comets that approach either the axon (green) or the dendrites (magenta) in either control (666 comets analysed across 13 movies) or Kinesin-2 RNAi (1058 comets analysed across nine movies) class I da neuron somas, as indicated. (D) Graph shows the % of comets that enter the axon (green) or the dendrites (magenta) as a proportion of those that had approached the axon in either control or Kinesin-2 RNAi class I da neuron somas, as indicated. (E) Graph shows the % of applicable comets that display turning events within either control (n = 257 comets across 13 movies) or Kinesin-2 RNAi (n = 386 comets across nine movies) class I da neuron somas, as indicated. (F) Graph shows the % of comets that are anterograde in the proximal primary dendrite (before any branches) in either control (n = 252 comets across 13 movies) or Kinesin-2 RNAi (n = 338 comets across nine movies) class I da neurons, as indicated. Error bars in (C–F) show the 95% confidence intervals.

While asymmetric nucleation from the somatic Golgi likely contributes to more microtubule plus ends reaching the axon (Figure 6) we also observed several occasions where microtubules turned towards the axon (Figure 7A; Figure 7—Video 1). Microtubule "collision resolution" events have been observed previously within dendritic branchpoints of da neurons, where the microtubules turn towards the soma along stable microtubules (Mattie et al., 2010; Weiner et al., 2016). This depends upon Kinesin-2, which is a heterotrimeric plus-end-directed motor whose regulatory subunit, Kap3, interacts with EB1 via APC (Mattie et al., 2010). It has been proposed that plus-end-associated Kinesin-2 guides growing microtubules along and towards the plus end of so-called ‘rail’ microtubules, as this can be recapitulated in vitro (Chen et al., 2014; Doodhi et al., 2014). When we depleted Kap3 from class I da neurons by RNAi there was a dramatic reduction in the frequency of microtubule turning events within the soma. In control cells, of the 257 comets across all movies that grew for more than 2 μm within the soma and that did not travel along the cell cortex, 165 displayed turning behaviour (64.2%), while across 9 Kap3 RNAi cells only 35 of the 386 qualifying comets displayed turning behaviour (9.1%) (Figure 7A,B,E; Figure 7—Videos 1 and 2; p<0.001). Comets in Kap3 RNAi cells tended to change direction only when travelling along the cell cortex or after collision with the nuclear envelope or cell cortex (Figure 7B; Figure 7—Video 2). As a result of reduced turning in Kap3 RNAi neurons, a lower proportion of comets reached the axon entry site and a higher proportion reached dendritic entry sites, compared to control cells: of the 1058 comets that originated within the soma of Kap3 RNAi cells, 97 approached the axon entry site (9.2%, compared to 15.6% in control neurons, p<0.001) and 114 approached a dendritic entry site (10.8%, compared to 7.1% in control neurons, p=0.0098) (Figure 7C). These data suggest that Kinesin-2 guides growing plus ends along pre-existing microtubules towards the axon and away from dendrites within the soma.

Comets that did arrive at the axon entry site could still readily enter the axon after Kap3 RNAi (Figure 7D); there was actually a ~ 1.3 fold increase compared to controls in the proportion of comets entering the axon (72.2% versus 53.5%, p=0.007). There is no requirement for Kinesin-2 for microtubule growth per se, which is presumably why microtubules can still enter once they reach the axon. It is unclear why entry is increased, but it is possible that Kinesin-2 may limit plus-end growth in general, although this purely speculative. Importantly, increased entry of growing microtubules into the axon has no major effect on microtubule polarity, as axons normally contain predominantly plus-end-out microtubules.

Most significantly, the proportion of comets that entered dendrites after Kap3 RNAi increased ~2 fold compared to controls, a much higher increase than that seen for axons. Of the 114 comets across nine movies that approached the entrance to a dendrite in Kap3 RNAi neurons, 65 entered (57.0%, compared to 27.7% in control neurons; p<0.001; Figure 7D). This affect was even more striking when knocking down a different Kinesin-2 component, Klp64D, where 56 of the 80 comets (across 10 movies) that approached a dendrite could enter (70.0%; p<0.001; Figure 7—Video 3). Increased entry of comets into dendrites contributed to, if not caused, a dramatic increase in the proportion of anterograde comets within proximal primary dendrites (prior to any dendritic branches): in control neurons, the vast majority of comets that we could observe in all proximal dendrites (88.9%) were retrograde (minus-end-out microtubules), while in Kap3 RNAi neurons the majority (63.6%) were anterograde (plus-end-out microtubules) (Figure 7F; p<0.001). An explanation for Kinesin-2 being required to prevent growing microtubules from entering dendrites may be that these microtubules need to grow past dendritic microtubules of opposite polarity. If plus-end-associated Kinesin-2 engages with these oppositely polarised microtubules it would presumably create a backward stalling force when trying to ‘walk’ towards the plus end of the dendritic microtubule (see discussion for more detail).

We conclude that Kinesin-2 is required to guide growing microtubule plus ends within the soma towards the axon and to prevent them from entering dendrites, which is essential in order to maintain minus-end-out microtubule polarity within proximal dendrites.

A model for microtubule regulation within the neuronal soma

Based on our observations, and the findings from previous studies (Chen et al., 2014; Doodhi et al., 2014; Mattie et al., 2010; Weiner et al., 2016), we propose a model to explain how microtubules are generated and regulated within the soma of da neurons, which also helps explain how microtubule polarity is promoted in axons and maintained within proximal dendrites (Figure 8). In this model, γ-TuRCs are localised to the cis-Golgi and microtubules are nucleated preferentially towards the axon, generating a polarised microtubule network within the soma. Plus-end-associated Kinesin-2 guides the growing plus ends of the nucleated microtubules along and towards the plus ends of the polarised microtubule network, and thus guides them towards the axon and away from dendrites (Figure 8A,C). Microtubules that happen to grow towards a dendrite are excluded from entering when the plus-end-associated Kinesin-2 engages with the shaft of a dendritic microtubule of opposite polarity and thus exerts a backward stalling force on the growing plus end (Figure 8B,C). Importantly, this model explains how minus-end-out microtubule polarity is maintained within proximal dendrites.

A model for microtubule nucleation and organisation within the soma of da neurons.

(A,B) Diagrams showing how plus-end-associated Kinesin-2 is predicted to induce turning of a growing microtubule along another microtubule when it approaches the other microtubule at an acute angle (A), or plus-end stalling when the growing microtubule approaches the other microtubules at an angle of ~180° (B). (C) A model depicting microtubule nucleation and growth within the soma of wild type (upper section) or Kinesin-2 depleted (lower section) da neurons. γ-TuRCs localise to the cis-Golgi (white) and nucleate microtubules preferentially towards the axon (i), creating a polarised microtubule network. In wild type neurons, plus-end-associated Kinesin-2 guides growing microtubules along this network towards the axon (ii). Growing microtubules readily enter axons (iii) but are excluded from entering dendrites (iv), because plus-end-associated Kinesin-2 engages with microtubules of opposite polarity, exerting a backward stalling force on the growing microtubule. In Kinesin-2 depleted neurons, microtubules nucleated from the somatic Golgi grow in straight lines (v) until contact with the nuclear envelope (vi) or the cell cortex (not depicted). Microtubules that approach dendrites can now readily enter (vii) resulting in a loss of overall minus-end-out microtubule polarity.

Discussion

Understanding of how neuronal microtubules are generated and organised is a matter of much interest and importance. In this paper, we have used Drosophila da neurons as an in vivo model system to address these questions. Our results have led us to propose a model that describes how microtubules are generated and organised within the soma, which also impacts the microtubule populations within proximal axons and dendrites. This model comprises multiple elements. Firstly, the model states that microtubules are nucleated asymmetrically from the somatic Golgi, growing initially with a preference towards the axon and away from dendrites. Secondly, plus-end-associated Kinesin-2 helps guide these growing microtubules towards the axon and away from dendrites along a polarised network of microtubules within the soma. Thirdly, plus-end-associated Kinesin-2 also helps prevent any microtubules that do approach the entrance to a dendrite from entering. We propose that a combination of these mechanisms is essential to maintain minus-end-out polarity in proximal dendrites, a key feature that distinguishes dendrites from axons.

We have shown that endogenously tagged γ-tubulin23C-GFP, which is a proxy for the major catalysts of microtubule nucleation, γ-TuRCs, localises predominantly to the Golgi stacks within the soma of da neurons, and to a few Golgi outposts within the proximal branches of class IV da neurons. Our data show that the ability of γ-tubulin to localise to these Golgi structures does not depend upon either Cnn or Plp, both of which have been implicated in recruiting γ-TuRCs to Golgi outposts within dendrites of class I and class IV da neurons, respectively (Ori-McKenney et al., 2012; Yalgin et al., 2015). Thus, γ-tubulin, presumably in the form of γ-TuRCs, must be recruited to the Golgi by another tethering protein, perhaps by one of the large coiled-coil ‘Golgin’ proteins that project from specific parts of the Golgi (Munro, 2011).

After showing that γ-tubulin-GFP localised to the somatic Golgi, we tracked EB1-GFP comets from the Golgi and found that they grew with an initial directional preference towards the axon, suggestive of asymmetric nucleation. This analysis was more robust under normal conditions than after cooling-warming cycles, because more comets could be analysed (it was difficult to keep the imaging plane consistent during temperature shifting, due to temperature-induced glass expansion/contraction). Thus, while an equal number of Golgi-derived comets (4) grew towards and away from the axon after warming in Figure 6—Video 2, we believe this perceived lack of asymmetry is most likely due to chance, especially as a fraction of comets can grow in more random directions even under normal conditions (Figure 6C). We therefore propose that there is a genuine preference for growth of Golgi-derived microtubules towards the axon. This may be explained, at least in part, by the asymmetric localisation of γ-tubulin at the somatic Golgi stacks. Using markers of cis- and trans-Golgi, we have found that γ-tubulin localises preferentially to the cis-Golgi. This is also true in mammalian cells, where the somatic Golgi acts as an asymmetric MTOC in various cell types, such as migrating fibroblasts and different types of cultured mammalian cells in interphase (Rios, 2014). It has been proposed that asymmetric microtubule nucleation is due to the presence of CLASP proteins at the trans-Golgi, which have been suggested to bind and stabilise the plus ends of microtubules that are nucleated by γ-TuRCs at the cis-Golgi (Vinogradova et al., 2009). Whether this occurs in Drosophila neurons remains to be explored. Drosophila CLASP is known to be a plus-tip protein within axons (Beaven et al., 2015) and is required for axon guidance (Lee et al., 2004), but to our knowledge a role for CLASP at the Golgi in any Drosophila cell type has not yet been reported. In mammalian cells, directional microtubule nucleation is thought to be important for cell motility in fibroblasts (Efimov et al., 2007) and for polarised pseudopod formation during invasion of cancer cells (Wu et al., 2016). Our data suggest that asymmetric nucleation at the somatic Golgi in Drosophila da neurons may establish a polarised microtubule network within the soma and is important for ensuring that plus-end-out microtubules enter axons rather than dendrites.

It is possible that a fraction of comets that originate from the somatic Golgi represent microtubules that were re-growing after partial depolymerisation, where the re-growth event happened to overlap a Golgi stack. However, several pieces of evidence suggest that the majority of the Golgi-derived comets represent nucleation events. First, γ-tubulin accumulates strongly at the somatic Golgi and a high accumulation of γ-TuRCs at a particular site is normally indicative of a nucleation site, such as when γ-TuRCs accumulate at mitotic centrosomes. Second, we have found that comets emerge repeatedly from the Golgi in a similar direction, strongly suggestive of repeated nucleation events. Third, we believe it is unlikely that all of the comets emerging from the Golgi after a cooling-warming cycle represent microtubules that had not fully depolymerised and that just happened to re-grow close to the Golgi. Moreover, comets that emerged from the Golgi a significant amount of time after warming did not emerge in the same direction as those that had grown immediately after warming. This strongly suggests they are not the same microtubule re-growing after depolymerisation but represent new nucleation events. Direct imaging of microtubules could help assess the degree of overall microtubule depolymerisation induced by cooling, although cold-resistant microtubules that may remain after cooling could impede the ability to visualise depolymerisation of dynamic microtubules, especially if the dynamic microtubules had originally grown alongside the stable microtubules. Increasing the cooling time before inducing regrowth may cause the depolymerisation of all microtubules, and this could be tested by using fluorescent markers of microtubules or by fixing and immunostaining the samples. These experiments have limitations, however, as keeping the animal alive for long enough to depolymerise all microtubule may be challenging and fixing and staining experiments do not allow one to observe the same neuron before, during, and after cooling. In summary, when we consider all of our data as a whole, we believe the most parsimonious conclusion is that microtubules are nucleated asymmetrically from the somatic Golgi.

It has previously been shown that centrosomes in Drosophila neurons do not act as MTOCs (Nguyen et al., 2011), and our observations that EB1-GFP comets do not emerge radially from a single source support this conclusion. In other cell types the somatic Golgi can ‘compete’ with centrosomes for the ability to organise microtubules, where decreasing nucleation from one organelle increases nucleation at the other (Gavilan et al., 2018; Ríos et al., 2004; Wu et al., 2016). It is therefore possible that the lack of microtubule nucleation at centrosomes in Drosophila neurons enables microtubules to be nucleated at the Golgi. In mammalian neurons the centrosome is deactivated after the first few days in culture (Stiess et al., 2010). An intriguing possibility is that this deactivation allows the Golgi to organise microtubules, which may be necessary to ensure correct microtubule polarity during later neuronal development, although nucleation from the Golgi in mammalian neurons has yet to be reported.

Our analysis was carried out in third instar larvae where the neurons are fully developed and functional. Axons have already extended and made connections in the central nervous system and dendritic arbors are largely established. It is thus somewhat surprising that microtubules continue to be nucleated within the soma. It is possible that somatic microtubules are necessary for transport of cargos to axonal and dendritic entry sites. Given that Golgi-derived microtubules grow preferentially towards the axon and that somatic Golgi stacks are distributed throughout the soma, there is likely an overall microtubule polarity within the soma itself, with more plus ends pointing towards the axon. Even small biases in the orientation of microtubules within a network can be important for the polarised distribution of components, such as in Drosophila oocytes (Zimyanin et al., 2008). A similar bias within neuronal soma could be important for directing molecules into axons and dendrites. Perhaps this asymmetric microtubule network within the soma, as well as the microtubules within the axon, need constant renewal. There is evidence that molecular motors can damage microtubules (Triclin et al., 2018) and so the large amount of motor-driven transport that occurs within neurons may necessitate microtubule renewal from the soma.

A key feature of our model is the action of plus-end-associated Kinesin-2. Our Kap3 RNAi data suggest that Kinesin-2 is required to guide growing microtubules along a polarised microtubule network within the soma towards the axon and away from dendrites, although future experiments with dual-colour imaging of microtubules and EB1-GFP comets will help support this conclusion. Our data also suggest that plus-end-associated Kinesin-2 prevents outward growing plus ends of somatic microtubules from entering dendrites. Within the soma, we envisage that when a somatic microtubule approaches another somatic microtubule at an acute angle (<90°), it can readily turn and be guided along that microtubule (Figure 8A,C). Kinesin-2 mediated "collision resolution" events occur at dendritic branch points in class I da neurons to ensure growing microtubules turn towards the soma (Weiner et al., 2016) and turning events have been recapitulated in vitro (Chen et al., 2014; Doodhi et al., 2014). One study showed that the in vitro turning events also occured at obtuse angles (>90°), where the growing microtubule buckled to allow the plus end to remain in contact with the ‘rail’ microtubule. This could presumably also occur within the soma of da neurons. The frequency of guidance events, however, decreases significantly as the angle increases (Doodhi et al., 2014). In contrast to the microtubule collision events that will occur with variable angles within the neuronal soma, when outward growing somatic microtubules try to grow into a dendrite they will always encounter dendritic microtubules at angles close to 180° (Figure 8B,C), because most dendritic microtubules are oriented minus-end-out and also because of the limited space available at dendrite entry points. Kinesin-2 motors on the plus end of the outward growing somatic microtubules could engage with the shafts of the minus-end-out dendritic microtubules and generate a backwards force when attempting to ‘walk’ towards the plus end of the dendritic microtubule i.e. in a direction opposite to which the plus end of the somatic microtubule is attempting to grow. This backward force would presumably lead to stalling of the plus end and thus depolymerisation of the microtubule. It is also possible that Kinesin-2 motors slide the plus end along the dendritic microtubule back into the soma, but this sliding action requires the growing microtubule to buckle and thus requires sufficient space (Doodhi et al., 2014). Thus, buckling may be impeded at the narrow dendrite entry site anddepolymerisation favoured. Kinesin-2 motors should be sufficient to induce stalling of microtubule growth, because growing microtubules generate a force of ~3–4 pN (Dogterom and Yurke, 1997), while a single Kinesin-2 motor generates a force of ~5 pN (Schroeder et al., 2012). Depolymerisation upon stalling could be equivalent to how depolymerisation is induced when microtubules grow against immovable objects (Janson et al., 2003). Importantly, this model elegantly explains why microtubules from the soma are prevented from growing into the dendrites while dendritic microtubules can readily grow into the soma. Other models, such as if a high concentration of a microtubule depolymerase was present at dendritic entry sites, could not distinguish between these two events. In contrast, our model predicts that dendritic microtubules can grow readily into the soma because they do not frequently encounter a microtubule with opposite polarity, except for the occasional somatic microtubule attempting to grow into a dendrite.

Our model explains how minus-end-out microtubule polarity is maintained within proximal dendrites, but what is the origin of minus-end-out microtubules? These microtubules could have been pushed out from the soma minus end first by motor-based sliding, a mechanism known to promote initial axon outgrowth in cultured Drosophila neurons (Lu et al., 2013; Lu et al., 2015). Alternatively, or in conjunction with this, they could have been nucleated at sites within dendrites and then have grown back towards the soma. Retrograde microtubule growth events do occur within the dendrites of da neurons, and some of these growth events originate from Golgi outposts (Ori-McKenney et al., 2012; Yalgin et al., 2015; Zhou et al., 2014) and from early endosomes at branchpoints (Weiner et al., 2020). It was shown that γ-tubulin co-localises with early endosome markers at class I branchpoints and that this localisation relies on Wnt signalling proteins (Weiner et al., 2020). Our observation that endogenously-tagged γ-tubulin localises to branchpoints supports this conclusion. Moreover, it was recently shown that an endosome-based MTOC tracks the growing dendritic growth cone within C. elegans PVD neurons and nucleates microtubules that travel back towards the soma (Liang et al., 2020). The authors also suggest that a similar process may occur in newly developing Drosophila class I neurons. We also observe γ-tubulin within dendritic bubbles and dendritic stretches, but whether γ-tubulin is also recruited to these regions by endosomes, or by cytosolic accumulations of γ-TuRC tethering proteins such as Cnn or Plp, will need to be addressed in future studies. While our data suggest that γ-TuRCs are absent from the majority of Golgi outposts, they appear to be present at a few proximal Golgi outposts within class IV neurons. Moreover, microtubule growth events from Golgi outposts could be independent of γ-TuRCs; other non-γ-TuRC microtubule binding proteins can promote microtubule nucleation in vitro (Roostalu and Surrey, 2017), and ectopic Golgi outposts within the axons of nudE mutants promote microtubule growth but not via γ-TuRCs (Arthur et al., 2015Yang and Wildonger, 2020). Thus, there are several potential mechanisms to generate minus-end-out microtubules within dendrites, that will need to be explored further in future.

It will be interesting in future to examine whether the plus ends of somatic microtubules can grow into dendrites more readily during early neuronal development, when there may be fewer minus-end-out microtubules within dendrites. If true, there must come a developmental point at which the balance shifts and microtubules are prevented from growing into dendrites. This shift could occur in several different ways, including upregulating the number of retrograde microtubules nucleated within dendrites, upregulating Kinesin-2, or changing the direction of microtubule nucleation within the soma. These are all interesting possibilities that are now open for investigation in the future.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional
information
Strain, strain background (Escherichia coli)5-alpha competent E. coliNEBC2987IHigh Efficiency chemically competent
Genetic reagent (Drosophila melanogaster)cnnf04547Exelixis at Harvard Medical SchoolExelixis:f04547; Flybase:FBst1019233FlyBase symbol: cnnf04547 ; Stock discontinued at the Exelixis and available from Conduit lab upon request.
Genetic reagent (D. melanogaster)plp5Bloomington Drosophila Stock CenterBDSC:9567; FLYB:FBst0009567; RRID:BDSC_9567FlyBase symbol: ru1 Plp5 st1/TM6C, Sb1 Tb1
Genetic reagent (D. melanogaster)plps2172Bloomington Drosophila Stock CenterBDSC:12089; Flybase:FBst0012089; RRID:BDSC_12089FlyBase symbol: ‘w[1118]; P{w[+mC]=lacW}Plp[s2172]/TM3, Sb[1]’
Genetic reagent (D. melanogaster)UAS-mCD8-RFPBloomington Drosophila Stock CenterBDSC:27392; Flybase:FBti0115769; RRID:BDSC_27392FlyBase symbol: ‘w[*]; P{w[+mC]=UAS-mCD8.ChRFP}3’
Genetic reagent (D. melanogaster)UAS-EB1-GFPBloomington Drosophila Stock CenterBDSC:35512; Flybase:FBti0141213; RRID:BDSC_35512FlyBase symbol: ‘w[*]; P{w[+mC]=UAS-EB1-GFP}3’
Genetic reagent (D. melanogaster)UAS-ManII-GFPBloomington Drosophila Stock CenterBDSC:65248; Flybase:FBti018367; RRID:BDSC_65248FlyBase symbol: ‘w[1118]; P{w[+mC]=UAS-ManII-EGFP}2; TM2/TM6B, Tb[1]’
Genetic reagent (D. melanogaster)UAS-ManII-mCherryOri-McKenney et al., 2012 (doi:10.1016/j.neuron.2012.10.008)Fly genotype: ‘w[1118]; P{w[+mC]=UAS-ManII-mCherry}/CyO’; gift from Yuh-Nung Jan
Genetic reagent (D. melanogaster)ppk-Gal4Bloomington Drosophila Stock CenterBDSC:32078; Flybase:FBti0127690; RRID:BDSC_32078FlyBase symbol: ‘w[*]; P{w[+mC]=ppk-GAL4.G}2’
Genetic reagent (D. melanogaster)ppk-Gal4Bloomington Drosophila Stock CenterBDSC:32079; Flybase:FBti013120; RRID:BDSC_32079FlyBase symbol: ‘w[*]; P{w[+mC]=ppk-GAL4.G}3’
Genetic reagent (D. melanogaster)221-Gal4Bloomington Drosophila Stock CenterBDSC:26259; Flybase:FBti011433; RRID:BDSC_26259FlyBase symbol: ‘w[*]; Pin[1]/CyO; P{GawB}221w-’
Genetic reagent (D. melanogaster)ppkCD4-tdGFPBloomington Drosophila Stock CenterBDSC:35842; Flybase:FBti014342; RRID:BDSC_35842FlyBase symbol: ‘w[1118]; P{w[+mC]=ppk-CD4-tdGFP}1b’
Genetic reagent (D. melanogaster)UAS-Dicer 2Bloomington Drosophila Stock CenterBDSC:24646; Flybase:FBti010143; RRID:BDSC_24646FlyBase symbol: P{w[+mC]=UAS-Dcr2.D}1,w[1118]
Genetic reagent (D. melanogaster)γ-tubulin37C RNAi; UAS-γ-tubulin37C RNAiBloomington Drosophila Stock CenterBDSC:32513; Flybase:FBti0132207; RRID:BDSC_32513FlyBase symbol: ‘y[1] sc[*] v[1] sev[21]; P{y[+t7.7] v[+t1.8]=TRiP.HMS00517}attP2’
Genetic reagent (D. melanogaster)Kap3 RNAi; UAS-Kap3 RNAiViennaDrosophila Resource CenterFBst0466097; VDRC ID:45400FlyBase symbol: ‘w1118;P{GD7377}v45400’
Genetic reagent (D. melanogaster)Klp64D RNAiViennaDrosophila Resource CenterFBst0466080; VDRC ID:45373FlyBase symbol: ‘w1118;P{GD7048}v45373’
Genetic reagent (D. melanogaster)γ-tubulin23c-sfGFPTovey and Conduit, 2018 (https://doi.org/10.1016/j.cub.2018.05.044)insertion of sfGFP with a 4X GlyGlySer linker at the C-terminus
Genetic reagent (D. melanogaster)γ-tubulin23c-eGFPThis paperinsertion of eGFP with a 4X Ser linker at the C-terminus. Generated by inDroso
Genetic reagent (D. melanogaster)sfGFP-Cnn-P1This paperinsertion of sfGFP with a 4X GlyGlySer linker at the start of exon 1a
Genetic reagent (D. melanogaster)sfGFP-Cnn-P2This paperinsertion of sfGFP with a 4X GlyGlySer linker at the start of exon 1b
Antibodyanti-GFP (mouse monoclonal)RocheCat# 11814460001; RRID:AB_390913IF(1:250)
Antibodyanti-Cnn (rabbit polyclonal)Lucas and Raff, 2007 (https://doi.org/10.1083/jcb.200704081)IF(1:1000); gift from Jordan Raff
Antibodyanti-Plp (rabbit polyclonal)Martinez-Campos et al., 2004 (https://doi.org/10.1083/jcb.200402130)IF(1:500); gift from Jordan Raff
Antibodyanti-Arl1 (chicken polyclonal)Torres et al., 2014 (doi:10.1242/jcs.122028)IF(1:200); gift from Sean Munroe
Antibodyanti-GM130 (rabbit polyclonal)AbcamCat# ab30637; RRID:AB_732675IF(1:300)
AntibodyAlexa-647 conjugated Hrp (goat polyclonal)JacksonJackson ImmunoResearch 123-605-021; RRID:AB_2338967IF(1:500)
AntibodyATTO-488 GFP-booster
(Camelid single domain ‘nanobody’)
Chromotekgb2AF488-10; RRID:AB_2827573IF(1:200)
Antibodyanti-Mouse IgG H and L Alexa Fluor 488 (goat polyclonal)AbcamCat# ab150117, RRID:AB_2688012IF(1:500)
Antibodyanti-Rabbit IgG H and L Alexa Fluor 568 (goat polyclonal)Thermo Fisher ScientificCat# A-11036, RRID:AB_10563566IF(1:500)
Recombinant DNA reagentpCDF3 (plasmid)AddgeneRRID:Addgene_49410pCFD3-dU6:3gRNA; gift from Simon Bullock
Recombinant DNA reagentpBluescript SK+ (plasmid)Simon Bullock labStandard cloning vector; gift from Simon Bullock
Recombinant DNA reagentpBS-KS-attB1-2-PT-SA-SD-2-sfGFP-FIAsh-StrepII-TEV-3x-FLAG (plasmid)Drosophila Genomics Resource CenterStock number:1314Vector used to amplify sf GFP sequence
Sequence-based reagentCnnNt_P1T2_fThis paperGuide oligoGTCGTGTTTAGACTGGTCCATGGG To generate Bbs1 cleavable fragment to clone into Bbs1 cut pCFD3 for Cnn promoter one tagging. Guide sequence underlined.
Sequence-based reagentCnnNt_P1T2_bThis paperGuide oligoAAACCCCATGGACCAGTCTAAACA; To generate Bbs1 cleavable fragment to clone into Bbs1 cut pCFD3 for Cnn promoter one tagging. Guide sequence underlined.
Sequence-based reagentCnnNt_P2T2_fThis paperGuide oligoGTCGTTAAATGAAACATAGAATA; To generate Bbs1 cleavable fragment to clone into Bbs1 cut pCFD3 for Cnn promoter two tagging. Guide sequence underlined.
Sequence-based reagentCnnNt_P2T2_bThis paperGuide oligoAAACTATTCTATGTTTCATTTAA; To generate Bbs1 cleavable fragment to clone into Bbs1 cut pCFD3 for Cnn promoter two tagging. Guide sequence underlined.
Sequence-based reagentcnn_UHA_P1_GFP_fThis paperPCR primersAAAGTTAACTATTTGAGGACCTCCCATGGTGTCCAAGGGCGAGGAG; used to amplify sfGFP with overhangs for HiFi cloning into pBS containing homology arms for for Cnn promoter 1
Sequence-based reagentcnn_DHA_P1_GFP_bThis paperPCR primersCCCGCAAAACCTGTTTAGACTGGTCGGATCCGCCGCTACCTCCGCTTCCACCGGAACCTCCCTTGTACAGCTCATCCATGCC; used to amplify sfGFP with overhangs for HiFi cloning into pBS containing homology arms for for Cnn promoter 1. Also contains sequence for 4X GlyGlySer linker
Sequence-based reagentcnn_UHA_P2_GFP_fThis paperPCR primersGCAAATGTTAAATGAAAGATACAATATGGTGTCCAAGGGCGAGGAG; used to amplify sfGFP with overhangs for HiFi cloning into pBS containing homology arms for for Cnn promoter 2
Sequence-based reagentcnn_DHA_P2_GFP_bThis paperPCR primersGTGAGGTAGATCGAAAGATACCCGCGGATCCGCCGCTACCTCCGCTTCCACCGGAACCTCCCTTGTACAGCTCATCCATGCC; used to amplify sfGFP with overhangs for HiFi cloning into pBS containing homology arms for for Cnn promoter 2. Also contains sequence for 4X GlyGlySer linker
Sequence-based reagentcnn_UHA_P1_fThis paperPCR primersGAAAGCTAAGCAGATTCTTCAGC; used to amplify upstream homology arm for promoter 1
Sequence-based reagentcnn_UHA_P1_bThis paperPCR primersGGGAGGTCCTCAAATAGTTAAC; used to amplify upstream homology arm for promoter 1
Sequence-based reagentcnn_DHA_P1_fThis paperPCR primersGACCAGTCTAAACAGGTTTTGC; used to amplify downstream homology arm for promoter 1
Sequence-based reagentcnn_DHA_P1_bThis paperPCR primersGCTCTCTGCACGTCCAAATAAAC; used to amplify downstream homology arm for promoter 1
Sequence-based reagentcnn_UHA_P2_fThis paperPCR primersCACTCGCTATAGTCTCGATCC; used to amplify upstream homology arm for promoter 2
Sequence-based reagentcnn_UHA_P2_bThis paperPCR primersATTGTATCTTTCATTTAACATTTGCGCTC; used to amplify upstream homology arm for promoter 2
Sequence-based reagentcnn_DHA_P2_fThis paperPCR primersGCGGGTATCTTTCGATCTACC; used to amplify downstream homology arm for promoter 2
Sequence-based reagentcnn_DHA_P2_bThis paperPCR primersTCCCGTGGAACAGGAACCAC; used to amplify downstream homology arm for promoter 2
Sequence-based reagentcnn_DHA_P1_pBS_fThis paperPCR primersCGGTTTATTTGGACGTGCAGAGAGCGGGGGATCCACTAGTTCTAGAG; used to amplify pBS backbone for promoter 1. Contains overhangs for HiFi cloning.
Sequence-based reagentcnn_UHA_P1_pBS_bThis paperPCR primersAAGCTGAAGAATCTGCTTAGCTTTCGGGCTGCAGGAATTCGATATC; used to amplify pBS backbone for promoter 1. Contains overhangs for HiFi cloning.
Sequence-based reagentcnn_DHA_P2_pBS_fThis paperPCR primersTTGCTGTGGTTCCTGTTCCACGGGAGGGGGATCCACTAGTTCTAGAG; used to amplify pBS backbone for promoter 2. Contains overhangs for HiFi cloning.
Sequence-based reagentcnn_UHA_P2_pBS_bThis paperPCR primersAAGTGGATCGAGACTATAGCGAGTGGGGCTGCAGGAATTCGATATC; used to amplify pBS backbone for promoter 2. Contains overhangs for HiFi cloning.
OtherLive imaging solutionThermo Fisher ScientificA14291DJLarvae imaging

Contact for reagent and resource sharing

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Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Paul Conduit (paul.conduit@ijm.fr).

Experimental model and subject details

All fly strains were maintained at 18 or 25°C on Iberian fly food made from dry active yeast, agar, and organic pasta flour, supplemented with nipagin, propionic acid, pen/strep and food colouring.

Drosophila melanogaster stocks

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The following fluorescent alleles were used in this study: γ-tubulin23C-sfGFP (Tovey et al., 2018), γ-tubulin23c-eGFP (this study), sfGFP-Cnn-P1 (this study), sfGFP-Cnn-P2 (this study), UAS-mCD8-mRFP (BL 27392), UAS-EB1-GFP (BL 35512), UAS-ManII-mCherry (Yuh-Nung Jan), and UAS-ManII-GFP (BL 65248). The following Gal4 lines were used in this study: ppk-Gal4 Chr II (B32078) and Chr III (BL 32079) and 221-Gal4 (BL 26259). The following mutant alleles were used in this study: plp5 (BL 9567), plps2172 (BL 12089), cnnf04547 (Exelixis at HMS), ppkCD4-tdGFP (BL 35842), KAP RNAi (VDRC 45400 GD), γ-tubulin37C RNAi (BL32513), Klp64D RNAi (VDRC 45373) UAS-Dicer 2 (BL 24646).

For examining the endogenous localisation of γ-tubulin23C we used flies expressing γ-tubulin23C-sfGFP and γ-tubulin23C-eGFP i.e. 2 copies of γ-tubulin23C-GFP, either alone or in combination with one copy of UAS-mCD8-RFP expressed under the control of one copy of either 221-Gal4 or ppk-Gal4. For examining the localisation of Cnn, we used flies expressing two copies of either sfGFP-Cnn-P1 or sfGFP-Cnn-P2 either alone or in combination with one copy of UAS-mCD8-RFP expressed under the control of one copy of either 221-Gal4 or ppk-Gal4. For examining the localisation of Plp in relation to medial Golgi, we used flies with one copy of UAS-ManII-GFP expressed under the control of one copy of either 221-Gal4 or ppk-Gal4. For examining the localisation of γ-tubulin23C in the absence of Cnn or Plp, we used flies expressing two copies of γ-tubulin23C-(sf/e)GFP (as above) in a cnnf04547/cnn f04547 or plp5/plps2172 mutant background. For examining microtubule dynamics in relation to the Golgi we used flies with one copy of UAS-EB1-GFP and one copy of UAS-ManII-mCherry, both expressed under the control of one copy of 221-Gal4. For examining microtubule dynamics in control neurons we used flies with one copy of UAS-EB1-GFP and one copy of UAS-γ-tubulin37C RNAi, with or without one copy of UAS-Dicer-2, expressed under the control of one copy of 221-Gal4. For examining microtubule dynamics in Kap3 RNAi neurons we used flies with one copy of UAS-EB1-GFP, one copy of UAS-Dicer-2, and one copy of UAS-Kap3 RNAi expressed under the control of one copy of 221-Gal4.

Method details

DNA cloning

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5-alpha Competent E. coli (High Efficiency) (NEB) cells were used for bacterial transformations, DNA fragments were purified using QIAquick Gel Extraction Kits (Qiagen), plasmid purification was performed using QIAprep Spin Miniprep Kits (Qiagen). Phusion High-Fidelity PCR Master Mix with HF Buffer (ThermoFisher Scientific) was used for PCRs.

Generating endogenously-tagged fly lines

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All endogenously-tagged lines were made using CRISPR combined with homologous recombination, by combining the presence of a homology-repair vector containing the desired insert with the appropriate guide RNAs and Cas9. The γ-tubulin23C-eGFP allele was generated by inDroso by initially inserting an SSSS-eGFP-3’UTR-LoxP-3xP3-dsRED-Lox P cassette before the selection markers were excised. The multi-serine insert acts as a flexible linker between γ-tubulin23C and eGFP. The following guide RNA sequences were used to cut either side of the 3’UTR: AGTCGATC|TGTGACCAGCGC and TTATGGTT|AATGTCGACTTG. The sfGFP-Cnn-P1 (insertion of sfGFP at the start of exon 1a) and sfGFP-Cnn-P2 (insertion of sfGFP at the start of exon 1b) alleles were generated within the lab following a similar approach to that used previously (Tovey et al., 2018). For GFP-Cnn-P1, flies expressing a single guide RNA containing the target sequence TGTTTAGACTGGTCCATGGG were crossed to nos-Cas9 expressing females and the resulting embryos were injected by the Department of Genetics Fly Facility, Cambridge, UK, with a pBluescript plasmid containing sfGFP and linker sequence (4X GlyGlySer) flanked on either side by 1.5 kb of DNA homologous to the cnn genomic locus surrounding the 5’ end of the appropriate coding region. The homology vectors were made by HiFi assembly (NEB) of PCR fragments generated from genomic DNA prepared from nos-Cas9 flies (using MicroLYSIS, Microzone) and a vector containing the sfGFP tag (DGRC, 1314). For GFP-Cnn-P2 flies, both the guide RNA containing the target sequence GTTAAATGAAACATAGAATA and the homology vector were injected into nos-Cas9 embryos (BL54591) by Rainbow Transgenic Flies, Inc Camarillo, CA 93012, USA. F1 and F2 males were screened by PCR using the following primers: for sfGFP-Cnn-P1: forward primer: AAAGTTAACTATTTGAGGACCTCCCATGGTGTCCAAGGGCGAGGAG; reverse primer: CCCGCAAAACCTGTTTAGACTGGTCGGATCCGCCGCTACCTCCGCTTCCACCGGAACCTCCCTTGTACAGCTCATCCATGCC; for sfGFP-Cnn-P2: forward primer: GCAAATGTTAAATGAAAGATACAATATGGTGTCCAAGGGCGAGGAG; reverse primer: GTGAGGTAGATCGAAAGATACCCGCGGATCCGCCGCTACCTCCGCTTCCACCGGAACCTCCCTTGTACAGCTCATCCATGCC.

Antibodies

The following primary antibodies were used: anti-GFP mouse monoclonal at 1:250 (Roche, 11814460001), anti-Cnn Rabbit polyclonal raised against first 660aa of Cnn-P1 (which includes amino acids 35–632 of Cnn-P2) at 1:1000 (Lucas and Raff, 2007), anti-Plp rabbit polyclonal at 1:500 (Martinez-Campos et al., 2004), Alexa-647 conjugated HRP polyclonal at 1:500 (Jackson), anti-Arl1 chicken polyclonal at 1:200 (gift from Sean Munro Torres et al., 2014), and anti-GM130 rabbit polyclonal at 1:300 (Abcam). The following secondary antibodies were used: ATTO-488 GFP-booster at 1:200 (Chromotek), Alexa-488 anti-Mouse at 1:500 (Abcam), Alexa-547 anti-Rabbit at 1:500 (ThermoFisher).

Immunostaining

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Larvae were dissected as described previously (Broadie and Bate, 1993). The fillet preparations were fixed in freshly prepared 4% formaldehyde for 20 min at room temperature and were then washed four times for 10 min in PBST (PBS + 0.1% TritonX-100). The preparations were then blocked in PBST + 5% BSA for 1 hr at room temperature and incubated with the appropriate primary antibodies diluted in PBST overnight at 4°C. After washing in PBST for ~8 hr, changing washes every 30–45 min, samples were incubated in secondary antibodies diluted in PBST overnight at 4°C. The fillet preparations were then washed for ~8 hr, changing washes every 30–45 min in PBST before mounting in Moviol. They were stored at −20°C and imaged within a week. Neurons within segments A2 to A6 were imaged; we observed no difference in the staining patterns between these segments.

Fixed and live cell imaging

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Imaging of all samples except for those expressing EB1-GFP in neurons or GFP-Cnn-P1 in embryos was carried out on an Olympus FV3000 scanning inverted confocal system run by FV-OSR software using a 60 × 1.4 NA silicon immersion lens (UPLSAPO60xSilcon). For live samples, wandering L3 larvae were placed in a drop of glycerol and flattened between a slide and a 22 × 22 mm coverslip, held in place by double-sided sticky tape, and imaged immediately. Imaging of EB1-GFP within da neurons and GFP-Cnn-P1 within embryos was performed on a Leica DM IL LED inverted microscope controlled by μManager software and coupled to a RetigaR1 monochrome camera (QImaging) and a CoolLED pE-300 Ultra light source using a 63X 1.3 NA oil objective (Leica 11506384). For EB1-GFP imaging, larvae were dissected in live imaging solution (ThermoFisher) to remove the majority of their tissues and mounted in Schneider’s medium supplemented with FBS and pen/strep between a slide and 22 × 22 mm coverslip held in place with tape and imaged immediately. When using the CherryTemp, the larvae were held between the CherryTemp chip and a 22 × 22 mm coverslip. The CherryTemp software was used to rapidly change the temperature of the liquid within the flow chamber from 20°C to 5°C after an initial 45 s of imaging. The temperature was then rapidly changed back to 20°C after a further 180 s and the neurons were imaged for a further 135 s. For EB1-GFP imaging, single Z-plane images were acquired every 5 s; for EB1-GFP/ManII-mCherry dual imaging single Z-plane images were acquired every 3 s. All images were processed using Fiji (ImageJ). EB1 comets were tracked using the Manual Tracking plugin in Fiji.

Quantification and statistical analysis

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Statistical analysis and graph production were performed using GraphPad Prism and SciStat.com.

To determine punctate versus diffuse localisation of γ-tubulin-GFP at branchpoints of class I da neurons, we visually categorised each branchpoint into one or other group depending on whether the puncta were clear and obvious or not. If they were clear and obvious, then they were categorised as puncta. If puncta and diffuse patches did co-exist we defined them as puncta. To quantify the number of Golgi outposts and γ-tubulin-GFP puncta per 100 μm dendrite we measured the total length of dendrites in ImageJ using the segmented line tool and marked and counted the number of Golgi outposts and γ-tubulin-GFP puncta. We then calculated their number per 100 μm dendrite. We did this across multiple images of different neurons. We analysed 14 class I neurons with a total dendritic length of 8525 μm and a total number of 183 branchpoints. We analysed 10 proximal and seven distal images of class IV da neurons with a total dendritic length of 3619 μm and 4489 μm, respectively, and a total number of 47 and 179 branchpoints, respectively.

For EB1-comet analysis, we excluded comets that were present within the first timepoint (and thus may not represent newly growing microtubules). The angle of initial comet growth was measured using the angle tool within ImageJ, by drawing lines from the axon entry site to the comet origin and then along the initial linear path of the comet. For the frequency distribution of comet angles in Figure 6B, the negative angles were made positive, so as not to distinguish between comets growing either side of the axon entry site, creating a distribution between 0° and 180°. A total of 163 comets from 59 Golgi stacks from 7 cells were analysed.

For the vector analysis in Figure 6C,D we used both positive and negative angles (between −180° and 180°). Initially, a vector for each comet was generated with a length of 1 by calculating cosine(angle) (Y value) and sin(angle) (X value). Taking in turn each Golgi stack that generated more than one comet, the vectors of each comet were added together to generate a resultant vector. These resultant vectors were then normalised by dividing their X and Y values by the number of comets originating from the Golgi stack, such that the maximum length of the resultant vector would be 1, irrespective of comet number. These normalised resultant vectors were plotted as circles on a scatter plot, with the size of each circle reflecting the number of comets originating from that particular Golgi stack. 44 Golgi stacks were analysed from seven neurons. We generated random sets of data by replacing each comet angle with a randomly generated number between −180 and 180 to show what results could be expected if the angles of comets originating from Golgi stacks were independent of each other and of the position of the axon (thus each random set of data was generated using 44 hypothetical Golgi stacks). We generated three random sets of data, the resultant vector length distributions of which are included in Figure 6D.

One-way Chi-squared tests were used to determine whether frequency distributions were significantly different from the distribution expected by chance i.e. whether they were different from random comet angles; a binomial probability calculator was used to determine the chance of observing the skewed distribution between upper (towards the axon) and lower (away from the axon) quadrants in the resultant vector scatter plot in Figure 6C.

To assess whether comets that originated within the soma approached and entered axons or dendrites, we defined a region (~0.5 μm wide) across the entrance to the axon or dendrite; any comets that entered this region were scored as comets that had approached; any comets that crossed this region were scored as comets that entered. For control neurons, we analysed a total of 666 comets (across 13 movies) that had originated during the movies within the soma (average of 10.0 comets per minute); for Kap3 RNAi we analysed a total of 1058 comets (across nine movies) (average of 20.0 comets per minute). Due to the labour-intensive nature of manual tracking we did not track all comets within the soma of Klp64D RNAi neurons; we instead focussed only on comets that approached dendrites (a total of 80 comets from 10 movies). To assess the polarity of dynamic microtubules within the proximal dendritic regions, we included both comets that originated within the proximal dendrite and those that grew into the dendrite from the soma. For control neurons, we analysed a total of 252 comets from 13 cells; for Kap3 RNAi we analysed a total of 338 comets from 9 cells. The overall proportion of comets that either turned, approached, entered or had anterograde polarity was plotted in Figure 7C–F along with the 95% confidence interval for each set of data. Sets of data were compared using one-way Chi-squared tests.

References

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Decision letter

  1. Yukiko M Yamashita
    Reviewing Editor; University of Michigan, United States
  2. K VijayRaghavan
    Senior Editor; National Centre for Biological Sciences, Tata Institute of Fundamental Research, India

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

This study describes microtubule nucleation at the somatic Golgi in the Drosophila neurons, which explains how microtubule polarity may be regulated in dendrites and axons. This is an important study that provides new insights into a long-standing observation of microtubule polarity in neurons. During the revision, the authors addressed reviewer concerns very well, also clearly stating what will be required to further test the functionality of microtubule nucleation at the somatic Golgi (and we fully recognize that localization-specific function of a given protein is difficult to prove for any given molecules). Also, circumstantial evidence provided in the paper is sufficiently strong to propose the function of Golgi-localized microtubule nucleation.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "Asymmetric nucleation and guidance maintain microtubule polarity within neurons" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

The reviewers appreciated the importance of the questions being addressed in the manuscript. However, both raised concerns on lack of functional analysis on the major part of the manuscript. As you can see in individual comments, the reviewers felt that addressing these concerns will be beyond the scope of straightforward revision permitted at eLife. However, we would be happy to reconsider your revised manuscript as a new submission if the major concerns are thoroughly addressed.

Reviewer #1:

This study addresses the important problem of microtubule organization in Drosophila dendrites using class I and class IV da neurons. Two main questions are addressed in the paper: (i) the nature of microtubule nucleation sites; (ii) polarity of growing microtubules. I would like to discuss these two questions separately.

1) Microtubule nucleation. The authors demonstrated that the majority of the nucleation events are happening at the γ-tubulin-containing Golgi outposts in class IV neurons and that localization of γ-TuRC to Golgi is independent of Centrosomin or Pericentrin-like protein. The paper contains good data demonstrating the nucleation on Golgi outposts, but I am not convinced that they clearly demonstrated that γ-TuRC localization to Golgi is independent of Cnn or Plp. Their conclusion is exclusively based on localization data, but it is not clear that the sensitivity of their colocalization techniques is sufficient for this conclusion. I would feel more confident if the microscopy results are supplemented with Cnn and Plp knock-down experiments in da neurons.

On a technical note here, the temperature shift experiment that they use to precisely localize microtubule nucleation sites is much less perfect than the authors believe. Most, if not all cells contain a sizable fraction of cold-stable microtubules (these microtubules are often acetylated). These microtubules by definition can survive the cold treatment and serve as nucleation sites when the temperature is shifted back, thus obscuring the correct location of nucleation sites in untreated neurons.

2) The polarity of the microtubule growth.

This part of the work extends the classical observation of Melissa Rolls and colleagues (Mattie et al., 2010) demonstrating that Kinesin-2 through EB1 and APC moves plus ends of growing microtubules toward plus ends of existing microtubules, thus promoting uniform polarity of microtubules.

The difference between this paper and the original paper and Mattie et al. is that here the authors are mostly looking at the growth of microtubules originated in the cell body and entering the axons while Mattie et al. studied uniform (minus-end-out) microtubule polarization in dendrites. Unfortunately, neither of these two papers addresses the key question of how the polarity in the dendrites and in the axons is first established, but only the question of how it is maintained. Whether the advances of this part of the manuscript justify its publication is not quite clear. What would make this part of the paper stronger is the imaging of EB1 and microtubules at the same time (the authors can label microtubules by tau-GFP or Jupiter-GFP) to show that EB1 on plus ends of growing microtubules indeed tracks pre-existing microtubules. In addition, the hypothesis that APC serves as a link between the two should be tested and discussed.

Furthermore, the microtubules in dendrites of da neurons span >100 μm distance, and there must be some de novo microtubule nucleation sites within the dendrites (outside of the soma). In addition to the somatic Golgi model, the authors should discuss these dendritic nucleation sites and their roles in maintaining the microtubule polarity in neurons.

Reviewer #2:

The authors describe some nice tools to look at endogenous microtubule regulators including γ-tubulin, Cnn and Plp. The first 6 figures are focused on trying to pin down sites of microtubule nucleation in Drosophila neurons using these tools. However, without any data on how the localization they see relates to nucleation (only Figure 6 tries to do this, and it needs substantial additional controls), it is difficult to know what the different spots, patches etc that they see mean. In Figure 7, behavior of growing microtubules in the cell body is analyzed, and here functional data is presented for the Kinesin-2 subunit Kap3. Overall it seems like two rather unrelated stories with functional data only for the second one. This is reflected in the Abstract, which is focused on the function of Kinesin-2, but not the figures, as only Figure 7 relates to this part of the story.

Major points:

1) The authors describe localization of γ-tubulin-GFP to puncta, diffuse spots, branch points and dendritic bubbles in Figures 1-5. The functional significance of these localizations is not clear and largely unexplored in the manuscript.

2) The first functional data is presented in Figure 6 with cold treatment of larvae to depolymerize microtubules. However, the key control of showing the treatment actually does depolymerize microtubules is missing.

3) The data in Figure showing that Kinesin-2 may help prevent microtubules growing into dendrites is intriguing but based on quite low numbers of events and only one RNAi condition. This part of the manuscript is not very closely related to the rest of the work.

Points on individual figures:

Figure 1: The authors distinguish γ-tub-GFP puncta and diffuse patches. How were these distinguished? Is it known whether one is more functionally relevant than the other? In the example images in B, which are puncta, and which are diffuse? I did not see a description of how the different types of signals were quantitated although numbers are mentioned in the text. In the legend it is noted that images in B and C are from living animals. It is a bit confusing whether A is also live. It looks like the signal in fixed neurons is more punctate than in live ones. Is this an accurate impression? If so, it would be good to mention in the text.

Figure 2: It looks like there is a movement artifact at the right side of the images in A and A' (double spots), so it might be good to choose a different example.

The authors conclude: "Collectively, our data show that Golgi outposts within class IV neuron branchpoints close to the soma frequently associate with γ-TuRCs," However, no data on γ-TuRCs was presented – are the authors assuming that the spots where they see γ-tubulin-GFP are γ-TuRCs? This claim should be supported either by looking at other γ-TuRC subunits or with functional analysis of nucleation.

While quantitation of Golgi and γ-tub-GFP is mentioned in the text, it is not clear how the quantitation was performed, and I could not find a description of it in the Materials and methods. It would be helpful to include graphs of the quantitation.

Figure 3. The authors stain γ-tubulin-GFP larvae with HRP and antibodies to GM130 and observed some intriguing patterns in the cell body. They conclude "this suggests that γ-tubulin-GFP localises on the rims of the cis-Golgi stack." It would be helpful to support this conclusion with other markers. Is the association with cis-Golgi higher than that with a trans-Golgi marker? Without labeling other parts of the Golgi, or surrounding structures like ER exit sites, it is hard to know whether the spots around the Golgi are most closely associated with cis-Golgi. It is particularly important to pin this down as Plp, which was previously shown to link nucleation sites to the Golgi, seems not to have a role here (Figure 5).

Figure 6. The authors examine the site of new EB1 comet formation in the cell body of class I neurons. How do they know which comets are the result of catastrophe rescue and which are nucleation? If they want to link comet formation to nucleation, it is important to show that it is altered in γ-tubulin mutants.

Some comets were determined to originate from the Golgi. The marker used for the Golgi was ManII, which earlier was described as not localizing cleanly to the Golgi in Class I neurons, which were used for this assay. Overall it is very difficult to know whether the new comets counted in this figure represent nucleation and whether they derive from the Golgi. A bias towards the axon would be very easy to explain based on catastrophe rescue of microtubules that derive from the dendrites, as these grow into the soma towards the axon.

For the microtubule cold depolymerization it is important to show that stable microtubules are actually depolymerized in neurons. They tend to be very refractory to cold or drug-induced depolymerization and unless stable microtubules really are eliminated by this treatment regrowth could be from remaining microtubules rather than nucleation. An additional confirmation that this assay is a good readout of nucleation would be to perform it in γ-tubulin mutant or knockdown neurons. Their statement "any comets that appear a significant amount of time after warming represent new nucleation events" requires significantly more validation. This section of the text also lacks references, for example on whether cold treatment has previously been shown to depolymerize neuronal microtubules.

Figure 7. The title of this section is "Kinesin-2-dependent plus-end turning and dendritic exclusion maintain microtubule polarity in axons and dendrites." Kinesin-2 also functions more distally in dendrites to control direction of microtubule growth. The section title attributes change in polarity to the cell body rather than this function. Can the data the authors present link dendrite polarity changes to a function in the cell body rather than in the dendrites? Is it because they only analyze the proximal dendrite?

There is no data on microtubule polarity in axons, although the section title states that Kinesin-2 has a role in maintaining axon microtubule polarity. Are there changes in axonal polarity in the Kap3 knockdown?

The major finding here, that comets normally do not grow easily in dendrites is interesting. It would be helpful to have stronger data to link Kap3 steering to keeping microtubules away from the dendrite; the increase in dendrite approaches is not quite significant (c). It would be very helpful to analyze more animals to see whether this will hold up, and the numbers of plus ends analyzed is quite low. The increase in successful entries into the dendrite (D) in the Kap3 RNAi is more convincing, but how does this relate to the model? Similarly, if Kinesin-2 was helping microtubules grow along parallel microtubules, would it not be expected that the successful entries into the axon in D would go down?

In the text the authors mention some additional data on turning within the cell body that is not shown in the figure. It would be good to have this in the figure as it adds additional support to the hypothesis that Kinesin-2 is functioning to control microtubule growth in the cell body.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Microtubules originate asymmetrically at the somatic Golgi and are guided via Kinesin2 to maintain polarity in neurons" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and K VijayRaghavan as the Senior Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.

Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in eLife, either of which would be linked to the original paper.

Summary:

This study describes microtubule nucleation at the somatic Golgi in the Drosophila neurons, which explains how microtubule polarity may be regulated in dendrites and axons. This is an important study that provides new insights into a long-standing observation of microtubule polarity in neurons.

This is a resubmission of a previously rejected paper. The authors addressed the concerns raised in the previous submission as much as possible, under covid-19 lockdown. One reviewer remains concerned that the functionality of Golgi-localized g-tubulin is not clearly demonstrated, but we recognize that this is generally a very difficult question to address (localization-specific function of a given protein). And other circumstantial evidence provided in the paper is sufficiently strong to propose the function of Golgi-localized microtubule nucleation.

Given the circumstance and the current editorial policy at eLife, we would like to invite to submit a revised version that addresses remaining reviewer concerns textually as much as possible. In the future, when the authors can obtain additional experimental data to support the conclusion, the paper should be amended by those new data.

Reviewer #1:

The authors have done everything they could under the current conditions. In normal times, I would certainly require simultaneous imaging of plus ends and a microtubule marker at the same time, this would make the paper much stronger. However, this type of imaging is not trivial, and it would be unfair to require it now. I think we can accept the manuscript.

Reviewer #2:

This manuscript is a resubmission of a previous version that was rejected. Unfortunately, the key functional experiments that were suggested in the previous comments were not performed because of Covid-related lab closure. While some leeway seems reasonable for manuscripts close to acceptance, asking key data to be overlooked for a rejected manuscript seems a stretch. While the authors were able to increase the n on one experiment and provide some additional staining, as they mention in the rebuttal many of the important experiments have not been done yet. Therefore, the limitations in the original submission remain.

Examples of key issues that have not been changed in the new version:

Much of the data remains descriptive without functional backup. For example, γ-tubulin localization to puncta vs diffuse concentrations is described, but it is not clear whether one type of localization is functional, or both are. Similarly, γ-tubulin is described as localizing to dendrite bubbles, and again this is unconnected to function.

Analysis of microtubule behavior in the cell body of γ-tubulin mutants is important to demonstrate that the comets initiating near Golgi are due to nucleation. In their live experiments with Golgi and EB1 (Figure 6) about half of the cell body looks like it is occupied by the Golgi marker. I did not see any quantitation to show that new comet formation is enriched on Golgi compared to other areas of cytoplasm. It is important to do this in control and γ-tubulin mutant animals.

The temperature shift assay remains difficult to interpret without additional information about what microtubules remain after cooling. There also does not seem to be quantitation in the figures to support conclusions made from this data.

https://doi.org/10.7554/eLife.58943.sa1

Author response

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Below we provide a detailed response to each of the reviewers’ comments, explaining how we have either directly addressed their concerns with new data or with detailed explanations within the text. These textual changes include clearer arguments as to why our data strongly supports our conclusions and also discussions of which future experiments will help further support the conclusions, as per eLife’s current publishing policy. In correspondence with the editors, we had highlighted aspects of the paper that reviewer 1 appeared to have misunderstood. Namely they stated that we had shown microtubule nucleation from Golgi outposts in class IV neurons. However, while we showed that γ-tubulin localises to a few proximal Golgi outposts in class IV neurons, our data showed microtubule nucleation from the somatic Golgi. In addition, experiments on γ-tubulin-GFP localisation in the absence of Cnn and Plp and additional discussion on dendritic microtubule nucleation were requested, however these were already present in the manuscript. In response to this, we were told that “reviewer #1 acknowledges that there was some misunderstanding on their part, thus the parts concerning this misunderstanding do not have to be addressed during the revision” – we have therefore excluded these comments from this rebuttal letter.

Reviewer #1:

This study addresses the important problem of microtubule organization in Drosophila dendrites using class I and class IV da neurons. Two main questions are addressed in the paper: (i) the nature of microtubule nucleation sites; (ii) polarity of growing microtubules. I would like to discuss these two questions separately.

1) Microtubule nucleation. The authors demonstrated that the majority of the nucleation events are happening at the γ-tubulin-containing Golgi outposts in class IV neurons and that localization of γ-TuRC to Golgi is independent of Centrosomin or Pericentrin-like protein. The paper contains good data demonstrating the nucleation on Golgi outposts, but I am not convinced that they clearly demonstrated that γ-TuRC localization to Golgi is independent of Cnn or Plp. Their conclusion is exclusively based on localization data, but it is not clear that the sensitivity of their colocalization techniques is sufficient for this conclusion. I would feel more confident if the microscopy results are supplemented with Cnn and Plp knock-down experiments in da neurons.

On a technical note here, the temperature shift experiment that they use to precisely localize microtubule nucleation sites is much less perfect than the authors believe. Most, if not all cells contain a sizable fraction of cold-stable microtubules (these microtubules are often acetylated). These microtubules by definition can survive the cold treatment and serve as nucleation sites when the temperature is shifted back, thus obscuring the correct location of nucleation sites in untreated neurons.

This point surrounds the main concern that we have not yet proven microtubules are nucleated from the somatic Golgi, which was also a concern of reviewer 2. So that we do not repeat ourselves, we detail our response to this main concern here.

Firstly, we have new experimental data that we believe supports our claim that the somatic Golgi nucleates microtubules. By staining different Golgi compartments, we have now convincingly shown that γ-tubulin localises asymmetrically to the cis-Golgi compartment of each Golgi stack (new Figure 3D). This fits with our observation that microtubules grow out asymmetrically from the somatic Golgi, further supporting our conclusion that the somatic Golgi nucleates microtubules asymmetrically. This is very similar to the situation in some mammalian cells, such as fibroblasts, where γ-tubulin localises asymmetrically to the cis-Golgi compartment within the soma and where microtubules are nucleated asymmetrically from the Golgi (see Rios, 2014 for a Review of the literature). We hope the reviewers agree that it would be surprising that the mammalian somatic Golgi but not the Drosophila da neuron somatic Golgi would nucleate microtubules when both recruit γ-tubulin in a similar fashion. Because the comparison to mammalian cells supports our conclusion, we have explained this clearly in the Discussion of the new manuscript.

Before the Covid-19 crisis, we had planned to directly address the reviewers’ concern by assessing the degree of microtubule depolymerisation during cold treatment within the cell bodies of neurons expressing Jupiter-mCherry, a microtubule binding protein. Clemens Cabernard kindly sent us a UAS-Jupiter-mCherry line, but unfortunately this did not arrive until 23rd March, after our University had closed.

In the absence of this new experimental data, we have therefore modified the text in the paper to be more cautious in interpreting our results, but we have also expanded our arguments to make it clearer that our current data, taken collectively, still strongly supports the conclusion that microtubules are nucleated from the somatic Golgi. While we still agree with the reviewers that stable microtubules may not have been depolymerised in our cooling-warming microtubule nucleation assay, one would expect that most highly dynamic microtubules (including those that were recently nucleated) would have been depolymerised by cold treatment. This prediction fits with the observation that EB1-GFP comets disappear immediately on cooling, which indicates the loss of their GTP-cap, which is required to prevent microtubule depolymerisation of a dynamic microtubule. Our results that several comets emerge from the Golgi stacks immediately after warming, and that these comets do not emerge from the same place that comets had stopped on cooling, is indicative that at least a fraction of microtubules are nucleated from the Golgi. It is surely unlikely that these comets could all represent re-growing stable microtubules that just happened to regrow from sites overlapping the Golgi.

In our opinion, the best evidence we have is that comets emerge from the Golgi over 50s after warming, and some of these comets do not emerge from the same Golgi that had generated a comet immediately after warming. The direction of all the late comets does not suggest that they were simply re-growing microtubules that had polymerised on warming, then depolymerised, and then had grown again from sites overlapping the Golgi. We realise that we had not made this clear in the first submission and so we have now done so in the new manuscript.

We also predict that many cold-stable acetylated microtubules would remain stable rather than become dynamic after cooling and re-warming. If true, they can essentially be ignored in this analysis. There is also an argument for not wanting to depolymerise all microtubules, as depolymerising all microtubules may result in an unusually high concentration of free tubulin that could, in theory, lead to nucleation from sites that do not normally nucleate microtubules under physiological conditions (Pickett-Heaps et al., 1982). Thus, to the best of our ability, we have used the cooling-warming microtubule nucleation experiment to complement our other data (asymmetric γ-tubulin localisation, asymmetric emergence of EB1-GFP comets from the Golgi) that strongly suggests microtubules are nucleated from the somatic Golgi. We have now included the experiment under its own sub-heading: “A Temperature-based microtubule nucleation assay suggests that microtubules are nucleated from the somatic Golgi in class I da neurons” to allow us to include our more expansive arguments.

Most importantly, our results from the cooling-warming assay should not be taken in isolation. We have also shown that γ-tubulin localises strongly to the somatic Golgi, that this localisation is asymmetric (new Figure 3D), and that EB1-GFP comets repeatedly grow out from Golgi stacks in a similar direction to each other (Figure 6). This is similar to what occurs in mammalian cells where it is well established that microtubules are nucleated from the somatic Golgi. Several papers investigating microtubule nucleation in da neurons have previously considered the emergence of comets from a single site, especially the repeated emergence of comets in a similar direction from the same site, as representative of nucleation (Zhou et al., 2014; Ori-McKenney 2014; Nguyen et al., 2014; Yalgin et al., 2015; Weiner et al., 2020). These studies did not robustly examine the localisation of endogenous γ-tubulin or perform cold-treatment experiments, so we have actually gone a step further in trying to establish genuine nucleation sites. Thus, while we have been unable to perform all requested experiments and while we cannot rule out other less likely possibilities as to why we see comets emerging from the Golgi, we can provide strong evidence to support our conclusions.

Nevertheless, we still appreciate the reviewers’ concern and have therefore made the following changes in the new manuscript:

– We have changed our title and Abstract to avoid using the word “nucleation” and to add elements of caution to our conclusions.

– We have modified the summary paragraph at the end of the Introduction to tone down our conclusion that the somatic Golgi nucleates microtubules: “…Tracking of EB1-GFP comets within the soma suggests that microtubules are nucleated asymmetrically from the somatic Golgi…”

– We have changed the Results title from “The somatic Golgi within da neurons nucleates microtubules asymmetrically” to “Growing microtubule originate asymmetrically from the somatic Golgi”.

– In the Results section we have more tentatively made the point that repeated growth from the same location in a similar direction is indicative of microtubule nucleation: “While not definitive, the similarity in the direction of comets emerging repeatedly from the same Golgi stack is indicative of consecutive microtubule nucleation events”.

– In the Results section we have modified “Cooling causes depolymerisation of dynamic microtubules and warming causes their regrowth from their nucleation site” to “Cooling typically causes depolymerisation of dynamic microtubules and warming causes their regrowth”.

– We have created a new section for the cooling-warming microtubule nucleation experiment to allow a more detailed analysis and discussion of the observations. This section is entitled: “A Temperature-based microtubule nucleation assay suggests that microtubules are nucleated from the somatic Golgi in class I da neurons”. This now includes discussing the possibility that a fraction of comets emerging after cooling-warming could have been from catastrophe-rescue of cold-stable microtubules. It also includes an expanded argument as to why the late emerging comets provide good evidence for nucleation from the Golgi.

– We have also substantially modified and expanded the discussion to make our arguments clearer, to discuss potential caveats with our experiments, and to discuss possible future experiments.

In addition, and with the reviewers concerns firmly in our minds, we want to make it clear that we plan to perform the additional experiments proposed in our originally appeal (testing microtubule depolymerisation on cooling and testing the effect of depleting γ-TuRCs on microtubule growth from the Golgi) and endeavour to publish the results in a follow up paper that will be linked to this current paper, as recommended in eLife’s new publishing guidelines.

2) The polarity of the microtubule growth.

This part of the work extends the classical observation of Melissa Rolls and colleagues (Mattie et al., 2010) demonstrating that Kinesin-2 through EB1 and APC moves plus ends of growing microtubules toward plus ends of existing microtubules, thus promoting uniform polarity of microtubules.

The difference between this paper and the original paper and Mattie et al. is that here the authors are mostly looking at the growth of microtubules originated in the cell body and entering the axons while Mattie et al. studied uniform (minus-end-out) microtubule polarization in dendrites. Unfortunately, neither of these two papers addresses the key question of how the polarity in the dendrites and in the axons is first established, but only the question of how it is maintained. Whether the advances of this part of the manuscript justify its publication is not quite clear. What would make this part of the paper stronger is the imaging of EB1 and microtubules at the same time (the authors can label microtubules by tau-GFP or Jupiter-GFP) to show that EB1 on plus ends of growing microtubules indeed tracks pre-existing microtubules.

This is a good point and we had planned to perform these experiments using the UAS-Jupiter-mCherry line sent by Clemens Cabernard. Alas, this has not been possible due to University closure. We have therefore added the following statement to the Discussion section: “Our Kap3 RNAi data suggests that Kinesin-2 is required to guide growing microtubules along a polarised microtubule network within the soma towards the axon and away from dendrites, although future experiments with dual-colour imaging of microtubules and EB1-GFP comets will help support this conclusion”. We propose to carry out this experiment when our University opens and to include the results in the follow up paper.

In addition, the hypothesis that APC serves as a link between the two should be tested and discussed.

Before University closure, Melissa Rolls had kindly sent us an APC RNAi line that she had previously published (Mattie et al., 2010), but she had cautioned that APC phenotypes are weak, perhaps due to a maternal contribution of APC protein (Mattie et al., 2010). Nevertheless, we managed to generate five videos before University closure and found that 48.1% comets enter dendrites. While this is nearly twice than in controls (now measured at 27.7% after increasing the N number), the difference is not quite significant at the 5% cut-off due to the low numbers (P=0.0775). We have therefore decided not to include this data in the new submission, preferring to add to the N number once the University re-opens and publish the results in the follow-up paper. We hope the reviewer’s will appreciate, however, that the difference is likely genuine and that the lack of significance is simply due to the low N-number for APC RNAi neurons.

Reviewer #2:

[…]

Major points:

1) The authors describe localization of γ-tubulin-GFP to puncta, diffuse spots, branch points and dendritic bubbles in Figures 1-5. The functional significance of these localizations is not clear and largely unexplored in the manuscript.

We agree with the reviewer that we have not demonstrated a functional role for the γ-tubulin accumulations within the dendrites. We reported these accumulations because we considered that, given the current controversy regarding the role of dendritic Golgi outposts and/or branchpoints as nucleation centres, it would be useful to the field if we reported in detail the endogenous localisation pattern of γ-tubulin within dendrites (something that has not been done before). We felt providing functional data for these dendritic γ-tubulin accumulations would go beyond the scope of this manuscript. Given the differential patterns observed within the dendrites of class I and class IV neurons, it will take a very careful and extensive analysis to understand and compare their roles. While Melissa Rolls has now published that γ-tubulin localises to endosomes in branchpoints, this is only within class I neurons and the vast majority of their γ-tubulin localisation data is from ectopically expressed γ-tubulin-GFP (only one image, using our own γ-tubulin-sfGFP line, is included in their supplementary data) (Weiner et al., 2020). In addition, our data also shows that γ-tubulin is not just restricted to branchpoints within dendrites but localises within dendritic stretches and dendritic bubbles in Class I neurons which has not been reported before. In fact, our quantification, which is the first of its kind, shows that most γ-tubulin accumulations are found outside of branchpoints in this neuron type. Our data is also the first to show clear endogenous γ-tubulin puncta associated with Golgi outposts in the proximal branchpoints of class IV neurons and makes it clear that this Golgi outpost associated γ-tubulin is restricted to these proximal branchpoints.

Collectively, robust analysis of endogenous γ-tubulin localisation in both class I and class IV neurons is of high value to the field. It will help explain the current controversy surrounding Golgi outposts and will provide important information for others to take into account in their future research. We therefore hope the reviewer agrees that it is worth keeping this data within the new submission.

We also point out that from Figures 3 onwards we are not just analysing these dendritic puncta, we are also analysing the somatic Golgi.

2) The first functional data is presented in Figure 6 with cold treatment of larvae to depolymerize microtubules. However, the key control of showing the treatment actually does depolymerize microtubules is missing.

We have summarised here several of the reviewers’ points that refer to their concern about whether our data proves that microtubules are nucleated from the somatic Golgi. We kindly refer the reviewer to the detailed discussion of this concern in the response to reviewer 1’s point 1 above.

3) The data in figure showing that Kinesin-2 may help prevent microtubules growing into dendrites is intriguing but based on quite low numbers of events and only one RNAi condition. This part of the manuscript is not very closely related to the rest of the work.

We had originally analysed 9 control and 6 Kap3 RNAi neurons. We therefore made and analysed four more control and three more Kap3 RNAi videos (now 13 control and 9 Kap3 RNAi videos in total) and this has increased the total number of comets approaching dendrites from 18 to 47 in controls and from 83 to 114 in Kap3 RNAi. Importantly, the percentage of comets that enter dendrites remains similar (a change from 22% to 28% in controls and from 59% to 57% in Kap3 RNAi) and the difference is still significantly different, supporting our model that plus end-associated Kinesin-2 is necessary for dendritic exclusion of outward growing microtubules. The new data is included in the new submission.

We have also now performed the experiment with a Klp64D RNAi line, which along with the Kap3 RNAi line has been validated previously (Mattie et al., 2010). From the ten Klp64D RNAi videos we have made there were 80 comets that approach dendrites and 56 entered (70.0%). We have therefore now reported this data in the new submission by including the following statement in the main text: “This affect was even more striking when knocking down a different Kinesin-2 component, Klp64D, where 56 of the 80 comets (across 10 videos) that approached a dendrite could enter (70.0%; p<0.001; Figure 7—video 3)”, as well as including an example video (new Figure 7—video 3).

In terms of whether this part of the manuscript is closely related to the rest of the work, it is of course closely related to Kinesin-2 mediated guidance of plus ends within soma (which has 2 facets: guidance towards the axon and exclusion of comets from dendrites). We believe the reviewer must therefore be referring to the work surrounding the localisation of γ-tubulin-GFP within the neurons, to which the reviewer refers to in comment 1 above. To help convince the reviewer that the work is related, we would like to explain the logical flow of our experiments: 1) We first analysed the localisation pattern of endogenous γ-tubulin-GFP within da neurons in an unbiased manner; 2) We found that γ-tubulin localised most strongly to the somatic Golgi rather than to sites within dendrites (although we document the differences in dendritic localisation between class I and class IV neurons); 3) We therefore tested whether the somatic Golgi nucleated microtubules by examining the growth of EB1-GFP comets within the soma – our data suggested that the Golgi did nucleate microtubules and that the microtubules were preferentially growing towards axons; 4) We therefore wondered what the fate of these microtubules may be, and found they tended to turn within the soma and grow into axons. In contrast, we also found that the microtubules that did happen to grow towards dendrites did not readily enter – we therefore wanted to know why; 5) We considered that Kinesin-2 plus end guidance might regulate both plus-end turning and exclusion from dendrites, as Kinesin-2 might engage with a polarised microtubule network within the soma to guide microtubules towards the axon, but might also engage with oppositely polarised microtubules at dendrite entry sites to generate a stalling force and depolymerisation of the outward growing microtubule; 6) We therefore depleted Kinesin-2 components, observing that Kinesin-2 was indeed necessary for both guiding microtubules towards axons and excluding them from dendrites.

Overall, we argue that this logic is sound and that the data is sufficiently related and of importance for the field of microtubule regulation in neurons to be published within the same paper.

Points on individual figures:

Figure 1: The authors distinguish γ-tub-GFP puncta and diffuse patches. How were these distinguished? Is it known whether one is more functionally relevant than the other? In the example images in B, which are puncta, and which are diffuse? I did not see a description of how the different types of signals were quantitated although numbers are mentioned in the text.

When quantifying, we visually categorised them into one or other group depending whether the puncta were clear and obvious or not. If they were clear and obvious, then they were categorised as puncta. If puncta and diffuse patches did co-exist, we defined them as puncta. We have now included a description of how we quantified the puncta and diffuse patches in the Materials and methods. In Figure 1B, all are diffuse except for the branchpoint on the far left of the panel. We do not know whether puncta or diffuse patches are more functionally relevant. It could be that both types localise to endosomes (as reported in Weiner et al., 2020) and the pattern of γ-tubulin depends simply on whether the endosomes are clumped together or more evenly spread. Some puncta may also localise to Golgi outposts, as we show in Figure 1D, but our data would suggest this is rare in class I.

In the legend it is noted that images in B and C are from living animals. It is a bit confusing whether A is also live. It looks like the signal in fixed neurons is more punctate than in live ones. Is this an accurate impression? If so, it would be good to mention in the text.

Figure 1A is also from a live specimen, and this was mentioned in the legend, but we now also mention it in the main text: “The most striking and obvious localisation of γ-tubulin-GFP within both class I and class IV neurons was as multiple large bright puncta within their soma (see images of living neurons in Figure 1A and Figure 2A, and of fixed and stained neurons in Figure 3A-C)”. The weak dendritic γ-tubulin-GFP signal can easily be missed, as it is close to background levels, and it is likely harder to see in fixed samples, potentially giving the impression that the signal in fixed neurons is more punctate. We do not see any obvious increase in the number of puncta in fixed images compared to live images. As we do not see a consistent difference, we have not mentioned anything on this point in the new submission.

Figure 2: It looks like there is a movement artifact at the right side of the images in A and A' (double spots), so it might be good to choose a different example.

The reviewer is correct, and we thank the reviewer for pointing it out. This movement is due to muscle contractions and is not unusual when imaging living animals. It tends to occur close to the segment boundaries. As the shift in this particular image is confined to the extreme right hand-side of the image, affecting only a small part of the neuron, we have cropped out the small region that had shifted.

The authors conclude: "Collectively, our data show that Golgi outposts within class IV neuron branchpoints close to the soma frequently associate with γ-TuRCs," However, no data on γ-TuRCs was presented – are the authors assuming that the spots where they see γ-tubulin-GFP are γ-TuRCs? This claim should be supported either by looking at other γTuRC subunits or with functional analysis of nucleation.

γ-tubulin is the most commonly used marker for γ-TuRCs, at least in part because of its high stoichiometry within the complex. γ-tubulin will normally represent γ-TuRCs – we do not know of any reports of γ-tubulin accumulations within cells that do not represent γ-TuRCs. But of course, we cannot rule out this possibility. We have recently managed to generate Grip91-sfGFP endogenously-tagged lines, but unfortunately we did not have time to fix, stain and image them prior to University closure. Nevertheless, while Grip91 is the protein with the next highest stoichiometry in the complex, it is not actually γ-TuRC specific as it is also present in γ-TuSCs (the smaller subcomplex of γ-TuRCs). To be sure of γ-TuRCs, it is therefore best to use a γ-TuRC-specific component, such as Grip75, Grip128, or Grip163, but these have a much lower stoichiometry and so the signal at the Golgi will be much weaker. Our initial observations of Grip75-GFP in living neurons that we were able to make before University closure suggested that the signal is very weak even at the somatic Golgi. Thus, rather than directly addressing this point experimentally, we have toned down the statement about γ-TuRCs localising to Golgi outposts, as well as only referring to the accumulation as “γ-tubulin” rather than “γ-TuRCs” throughout the preceding paragraph. The statement at the end of the paragraph now reads: “Collectively, our data show that Golgi outposts within class IV neuron branchpoints close to the soma frequently associate with γ-tubulin, but that the majority of Golgi outposts do not. Whether this proximal Golgi outpost associated γ-tubulin represents fully functional γ-TuRCs remains to be tested.”

While quantitation of Golgi and γ-tub-GFP is mentioned in the text, it is not clear how the quantitation was performed, and I could not find a description of it in the Materials and methods. It would be helpful to include graphs of the quantitation.

We apologise for not including this in the original submission. We have now included the details in the Materials and methods of the new submission. We thought that adding graphs would make the figures more crowded than they needed to be and so have not included them. We are willing to do so, however, should the reviewer deem it absolutely necessary.

Figure 3. The authors stain γ-tubulin-GFP larvae with HRP and antibodies to GM130 and observed some intriguing patterns in the cell body. They conclude "this suggests that γ-tubulin-GFP localises on the rims of the cis-Golgi stack." It would be helpful to support this conclusion with other markers. Is the association with cis-Golgi higher than that with a trans-Golgi marker? Without labeling other parts of the Golgi, or surrounding structures like ER exit sites, it is hard to know whether the spots around the Golgi are most closely associated with cis-Golgi. It is particularly important to pin this down as Plp, which was previously shown to link nucleation sites to the Golgi, seems not to have a role here (Figure 5).

We agree with the reviewer and have stained γ-tubulin-GFP larvae with HRP and antibodies against GM130 (cis-Golgi) and Arl1 (trans-Golgi) and obtained four channel images. The new data clearly shows that Arl1 is offset from both γ-tubulin-GFP and GM130, which overlap (new Figure 3D). While we used the HRP signal to identify neurons during analysis, we have not included this channel in the new figure for simplicity. Now that we are more certain that γ-tubulin localises to the cis-Golgi, we have also slightly modified the cartoon images of Golgi stacks in our model figure, now Figure 8C.

We make the point again here that now we have proof of the asymmetric localisation of γ-tubulin to the cis-Golgi, we can be more certain that the somatic Golgi nucleates microtubules, as the asymmetric localisation fits well with the observed asymmetric microtubule growth from the Golgi stacks, which is known to also occur in mammalian cells.

Figure 6. The authors examine the site of new EB1 comet formation in the cell body of class I neurons. How do they know which comets are the result of catastrophe rescue and which are nucleation? If they want to link comet formation to nucleation, it is important to show that it is altered in γ-tubulin mutants.

We agree that this would have been a nice experiment and we had planned to deplete γ-TuRCs and examine the effect on EB1-GFP comets. Alas, the University closed while the fly lines for this experiment were still being generated. It is important to note, however, that this experiment may not technically be possible. Our past experience has shown that effectively depleting γ-TuRCs within larval da neurons can be challenging. We believe this is due to a maternal contribution of γ-tubulin-37C, because we know that γ-tubulin-23C null mutant larvae can live up until the end of the third instar larval stage (unpublished observations). The persistence of maternal γ-tubulin-37C is consistent with results from other groups where attempts to reduce γ-tubulin-23C in class I da neurons have not produced dendritic morphology defects (Nguyen et al., 2014; Weiner et al., 2020), even though γ-tubulin has now been proposed to function at branchpoints in class I neurons (Weiner et al., 2020). Nevertheless, we plan to perform this experiment after the University re-opens and include the results in a future follow-up paper.

Some comets were determined to originate from the Golgi. The marker used for the Golgi was ManII, which earlier was described as not localizing cleanly to the Golgi in Class I neurons, which were used for this assay. Overall it is very difficult to know whether the new comets counted in this figure represent nucleation and whether they derive from the Golgi.

While UAS-ManII-GFP is not a reliable marker of Golgi outposts within class I dendrites, it always colocalises with HRP within the soma. We therefore now show an example of this in the new Figure 1—figure supplement 1D. Thus, UAS-ManII does mark genuine Golgi structures in the soma, validating its use in the comet analysis.

A bias towards the axon would be very easy to explain based on catastrophe rescue of microtubules that derive from the dendrites, as these grow into the soma towards the axon.

We thank the reviewer for pointing this out and it is a caveat we have highlighted in the new manuscript. Nevertheless, we make our view clear that we believe the effect is minimised by analysing only those comets that originate from the Golgi: “While it is possible that the direction of comet growth can be influenced by comets growing into the soma from the dendrites, which will tend to grow towards the axon, we minimised this effect by quantifying only those comets that originate from Golgi stacks. The comets we analysed are therefore more likely to represent true growth events from the Golgi rather than catastrophe and regrowth of microtubules that originated from dendrites.”

For the microtubule cold depolymerization it is important to show that stable microtubules are actually depolymerized in neurons. They tend to be very refractory to cold or drug-induced depolymerization and unless stable microtubules really are eliminated by this treatment regrowth could be from remaining microtubules rather than nucleation. An additional confirmation that this assay is a good readout of nucleation would be to perform it in γ-tubulin mutant or knockdown neurons. Their statement "any comets that appear a significant amount of time after warming represent new nucleation events" requires significantly more validation.

We agree with the reviewer that we had not made this point clearer in the original paper, and this comment made us realise that we needed to explain ourselves better, especially as we feel this observation is one of the strongest p. We have therefore removed the original sentence and included instead a detailed explanation within the Results section: “In our opinion, the best evidence for microtubule nucleation occurring at the somatic Golgi comes from the observation that several comets emerged from Golgi stacks relatively late after warming. […] This strongly suggests that these late emerging comets represent genuine nucleation events from the Golgi, although it is impossible to rule out that they could have been generated by regrowing microtubules that were originally out of focus.”

This section of the text also lacks references, for example on whether cold treatment has previously been shown to depolymerize neuronal microtubules.

To our knowledge, this has not been tried in Drosophila neurons in vivo, although cold-induced depolymerisation has been carried out in other cell types. Of note, cold-stable microtubules exist within mammalian neurons, but this relies on MAP6, which is restricted to vertebrates (see Delphin et al., 2012, JBC). We have therefore now included the following statement and citations in the Results section: “Cooling-warming microtubule nucleation assays have previously been performed in various systems, including Drosophila embryos (Hayward et al., 2014), Drosophila S2 cells (Bucciarelli et al., 2009), and in mammalian cells (Torosantucci et al., 2008). […] We therefore presumed that cooling would result in the depolymerisation of dynamic microtubules within Drosophila neurons, allowing us to correlate the position of new comet growth with nucleation sites.”

Figure 7. The title of this section is "Kinesin-2-dependent plus-end turning and dendritic exclusion maintain microtubule polarity in axons and dendrites." Kinesin-2 also functions more distally in dendrites to control direction of microtubule growth. The section title attributes changes in polarity to the cell body rather than this function. Can the data the authors present link dendrite polarity changes to a function in the cell body rather than in the dendrites? Is it because they only analyze the proximal dendrite?

Yes, this is because we only analyse the proximal dendrite. This was mentioned in the figure legend, but we now realise that we need to make this clear in the main text, and that we also need to change the section title to more adequately reflect our findings. We have changed the title to: “Growing microtubules within the soma are guided towards the axon while being excluded from entering dendrites in a Kinesin-2-dependent manner”. We have also changed the final concluding statement to read: “We conclude that Kinesin-2 is required to guide growing microtubule plus ends within the soma towards the axon and to prevent them from entering dendrites, which is essential in order to maintain minus-end-out microtubule polarity within proximal dendrites.”

There is no data on microtubule polarity in axons, although the section title states that Kinesin-2 has a role in maintaining axon microtubule polarity. Are there changes in axonal polarity in the Kap3 knockdown?

We apologise for not making ourselves clearer. We believe there is a role for promoting plus-end out polarity in axons because Kinesin-2 guides the growing microtubules towards axons, which should in theory lead to more microtubules growing into the axon and contributing to the plus-end-out pool. We agree, however, that there is no obvious effect on axon polarity in Kap3 RNAi and have therefore removed the reference to the axon in the section title. The title is now: “Growing microtubules within the soma are guided towards the axon while being excluded from entering dendrites in a Kinesin-2-dependent manner”.

The major finding here, that comets normally do not grow easily in dendrites is interesting. It would be helpful to have stronger data to link Kap3 steering to keeping microtubules away from the dendrite; the increase in dendrite approaches is not quite significant (c). It would be very helpful to analyze more animals to see whether this will hold up, and the numbers of plus ends analyzed is quite low.

We agree and have now analysed more control (13) and Kap3 RNAi (9) neurons. With the increased number of comets available to analyse, the difference between the proportion of comets approaching dendrites in control (7%) versus Kap3 RNAi (11%) is now significant (p=0.0098). We can therefore conclude that Kinesin-2 is required to prevent growing microtubules from entering dendrites but is also required to steer growing microtubules away from dendrites in the first place. We now refer to this result within the Results and Discussion.

The increase in successful entries into the dendrite (D) in the Kap3 RNAi is more convincing, but how does this relate to the model?

This actually agrees perfectly with the model and is, to us, the most important result of the paper. This comment made us realise that we need to explain our model much more clearly in the new submission. We have therefore placed the model in a new Figure 8, that also includes a new section (Figure 8A, B) to help explain how Kinesin-2 differentially regulates plus end growth in different contexts, and we have also included an expanded discussion of the model in the Discussion in the paragraph starting: “A key feature of our model is the action of plus-end associated Kinesin-2”

Similarly, if Kinesin-2 was helping microtubules grow along parallel microtubules, would it not be expected that the successful entries into the axon in D would go down?

While Kinesin-2 may guide microtubules along parallel microtubules, there is no requirement for Kinesin-2 in microtubule growth per se. Rather, Kinesin-2 is required for microtubules to engage with and turn along the path of the other microtubules (i.e. when guided towards the axon entry site), and also to prevent microtubules growing parallel to oppositely polarised microtubules (i.e. preventing them from entering dendrites). Once a microtubule has reached the axon entry site, its growth into the axon should in theory not require Kinesin-2, which fits with our data. With our new increased N number, we find that the moderate increase in the number of comets that enter the axon in Kap3 RNAi neurons is actually statistically significant. While this increase is not as dramatic as the increase in dendrite entry, we feel it also deserves an explanation. We have therefore included the following statement in the new submission: “Comets that did arrive at the axon entry site could still readily enter the axon after Kap3 RNAi (Figure 7D); there was actually a ~1.3-fold increase compared to controls in the proportion of comets entering the axon (72.2% versus 53.5%, p=0.007). […] Importantly, increased entry of growing microtubules into the axon has no major effect on microtubule polarity, as axons normally contain predominantly plus-end-out microtubules.”

In the text the authors mention some additional data on turning within the cell body that is not shown in the figure. It would be good to have this in the figure as it adds additional support to the hypothesis that Kinesin-2 is functioning to control microtubule growth in the cell body.

I think the reviewer may have missed this data – it is included as a graph in Figure 7E.

[Editors’ note: what follows is the authors’ response to the second round of review.]

Reviewer #1:

The authors have done everything they could under the current conditions. In normal times, I would certainly require simultaneous imaging of plus ends and a microtubule marker at the same time, this would make the paper much stronger. However, this type of imaging is not trivial, and it would be unfair to require it now. I think we can accept the manuscript.

This reviewer felt that the paper could now be accepted but would have liked to see simultaneous imaging of plus ends and a microtubule marker. We refer to the importance of this experiment in the Discussion: “A key feature of our model is the action of plus-end-associated Kinesin-2. Our Kap3 RNAi data suggests that Kinesin-2 is required to guide growing microtubules along a polarised microtubule network within the soma towards the axon and away from dendrites, although future experiments with dual-colour imaging of microtubules and EB1-GFP comets will help support this conclusion.” We plan to do this experiment in the near future, by imaging EB1-GFP in a Jupiter-mCherry background and include the results in the proposed eLife advance paper.

Reviewer #2:

This manuscript is a resubmission of a previous version that was rejected. Unfortunately, the key functional experiments that were suggested in the previous comments were not performed because of Covid-related lab closure. While some leeway seems reasonable for manuscripts close to acceptance, asking key data to be overlooked for a rejected manuscript seems a stretch. While the authors were able to increase the n on one experiment and provide some additional staining, as they mention in the rebuttal many of the important experiments have not been done yet. Therefore, the limitations in the original submission remain.

When this reviewer wrote their independent review, they still had certain reservations about the lack of functional data for our observations of γ-tubulin localisation within dendrites and our conclusion that microtubule nucleation occurs at the somatic Golgi. These concerns are similar to their original concerns that we were unable to fully address due to the 3-month lockdown period. As requested, below we address these concerns textually as best possible and highlight the textual changes we have made in the manuscript (several of which were already present in the re-submitted paper). We also highlight the experiments that we plan to include in the aforementioned eLife advance paper.

Examples of key issues that have not been changed in the new version:

Much of the data remains descriptive without functional backup. For example, γ-tubulin localization to puncta vs diffuse concentrations is described, but it is not clear whether one type of localization is functional, or both are. Similarly, γ-tubulin is described as localizing to dendrite bubbles, and again this is unconnected to function.

Our data on γ-tubulin-GFP localisation within dendritic arbors is the first to fully describe and carefully quantify the localisation pattern of endogenously-expressed γ-tubulin within class I and class IV da neurons. We did not provide any functional data for these observations because this would go beyond the scope of the paper, which focusses on microtubule regulation within the soma of these neurons. Nevertheless, we strongly believe that quantifying and comparing the localisation of endogenously-tagged γ-tubulin-GFP within the dendrites of class I and class IV da neurons is important and should be reported to the community, particularly due to the ongoing debate over whether Golgi outposts act as MTOCs or not. Given the reviewer’s continued concern, we now specifically mention in the Results section that we lack functional data for these observations: “Nevertheless, this dendritic localisation that we observe likely represents the recently reported recruitment of γ-tubulin to endosomes at branchpoints (Weiner et al., 2020)” to “It is possible that the localisation of endogenous γ-tubulin-GFP at branchpoints represents the recently reported recruitment of γ-tubulin to endosomes at branchpoints that provide a platform for microtubule nucleation (Weiner et al., 2020). We have not tested here, however, whether the diffuse or punctate γ-tubulin-GFP signals, or both, are functionally important at branchpoints.” and we have added “It remains to be tested whether the accumulation of γ-tubulin within these bubbles is functionally relevant.”

Analysis of microtubule behavior in the cell body of γ-tubulin mutants is important to demonstrate that the comets initiating near Golgi are due to nucleation. In their live experiments with Golgi and EB1 (Figure 6) about half of the cell body looks like it is occupied by the Golgi marker. I did not see any quantitation to show that new comet formation is enriched on Golgi compared to other areas of cytoplasm. It is important to do this in control and γ-tubulin mutant animals.

This comment relates to the reviewer’s continued concern as to whether the observed asymmetric localisation of γ-tubulin at the somatic Golgi, asymmetric microtubule growth from the somatic Golgi, and emergence of microtubule growth after cooling-warming from the somatic Golgi, is really representative of microtubule nucleation from the somatic Golgi. While the Editors’ view is that “we recognize that this is generally a very difficult question to address (localization-specific function of a given protein). And other circumstantial evidence provided in the paper is sufficiently strong to propose the function of Golgi-localized microtubule nucleation” we would still like to respond to the reviewer’s comment and highlight the textual changes we have made to the manuscript.

We agree with the reviewer that it will be important in future to try to deplete γ-TuRCs (something that is not trivial, as discussed in our last rebuttal) and then assess whether there is a reduction in comets emerging from the Golgi. We plan to perform this experiment in the near future, once the fly stocks are ready, and include the results in the proposed eLife advance paper. We think that comparing the frequency of comets emerging from the Golgi versus those emerging within the cytosol in wild-type neurons will not necessarily help determine whether microtubules are nucleated from the Golgi for at least two reasons. Firstly, Augmin-mediated nucleation could be occurring from the side of microtubules within the cytosol in addition to nucleation from the Golgi. If the rate of nucleation via Augmin was relatively high, this might make it appear that comets emerging from the Golgi were less significant, even if they were also being nucleated from the Golgi by γ-TuRCs. We mention the possibility of Augmin-mediated nucleation. Secondly, the results will be affected by plus-end dynamics post-nucleation i.e. the rate of catastrophe-rescue events where a microtubule partially depolymerises and then re-grows. We observe comets with relatively short tracks within the soma, indicating that the microtubules can be highly dynamic. This could lead to a relatively high frequency of new comets emerging within the cytosol (due to regrowth events), even if all microtubules were nucleated only from the Golgi. As mentioned in our last rebuttal, the fact that comets emerge asymmetrically from the Golgi (coupled with the asymmetric localisation of γ-tubulin at the Golgi), and that multiple comets emerging from the same Golgi stack emerge in a similar direction, lends strong support to the idea that microtubules are indeed nucleated from the Golgi.

We had already made several textual changes in our re-submitted paper that show we are being cautious about our conclusion that microtubules are nucleated from the somatic Golgi:

– In the title and Abstract we use the term “microtubules originate” rather than saying “microtubules are nucleated” when referring to the somatic Golgi.

– Results: “While not definitive, the similarity in the direction of comets emerging repeatedly from the same Golgi stack is indicative of consecutive microtubule nucleation events.”

– Discussion: “the model states that microtubules are nucleated asymmetrically from the somatic Golgi”. The important point being that this is a model and not a statement of fact.

– Discussion: “After showing that γ-tubulin-GFP localised to the somatic Golgi, we tracked EB1-GFP comets from the Golgi and found that they grew with an initial directional preference towards the axon, suggestive of asymmetric nucleation”.

– Discussion: “It is possible that a fraction of comets that originate from the somatic Golgi represent microtubules that were re-growing after partial depolymerisation, where the re-growth event happened to overlap a Golgi stack. However, several pieces of evidence suggest that the majority of the Golgi-derived comets represent nucleation events…”

– Discussion: “In summary, when we consider all of our data as a whole, we believe the most parsimonious conclusion is that microtubules are nucleated asymmetrically from the somatic Golgi.”

The temperature shift assay remains difficult to interpret without additional information about what microtubules remain after cooling. There also does not seem to be quantitation in the figures to support conclusions made from this data.

We agree that it will be important to test the extent of microtubule depolymerisation during cooling, and we plan to do this experiment in the near future, reporting the results in the eLife advance paper. Nevertheless, interpreting what happens to microtubules during cooling may be problematic due to a likely mix of stable (cold-insensitive) and dynamic (cold-sensitive) microtubule populations. We explained this in our last rebuttal and mention it in the manuscript. While there is no quantification in the figures (it is difficult to get sufficient numbers due to the thermal fluctuations leading to loss of the focal plane during temperature transitions, which is mentioned in the Discussion, we now report the following numbers in the text: “Within 20s of warming in Figure 6—video 2, 4 comets emerged from Golgi structures (green-labelled comets, Figure 6E; Figure 6—video 2), while 2 comets emerged away from the Golgi (purple-labelled comets, Figure 6E; Figure 6—video 2). During the 2 minutes and 12 seconds between warming and the end of the video, a total of 8 comets emerged from the Golgi with 5 emerging from non-Golgi sites.” We go on to postulate that the non-Golgi associated comets that emerge initially after warming could be due to Augmin mediated nucleation, Golgi-nucleated comets that emerge into the focal plane post nucleation, or re-growing microtubules that had not fully depolymerised. This text remains unchanged from the last version.

We also want to point out the textual changes we had already made to the re-submitted paper that show we are being cautious about our interpretation of the cooling-warming assay:

– Results: “When the appropriate focal plane was reached shortly after warming, we could observe EB1-GFP comets emerging from the ManII-mCherry-labelled Golgi structures (green-labelled comets, Figure 6E; Figure 6—video 2), suggestive of Golgi-located microtubule nucleation events.”

– Results: “This strongly suggests that these late emerging comets represent genuine nucleation events from the Golgi, although it is impossible to rule out that they could have been generated by re-growing microtubules that were originally out of focus.”

https://doi.org/10.7554/eLife.58943.sa2

Article and author information

Author details

  1. Amrita Mukherjee

    Department of Zoology, University of Cambridge, Cambridge, United Kingdom
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
  2. Paul S Brooks

    Department of Zoology, University of Cambridge, Cambridge, United Kingdom
    Contribution
    Resources, Data curation, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  3. Fred Bernard

    Université de Paris, CNRS, Institut Jacques Monod, Paris, France
    Contribution
    Resources
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7919-253X
  4. Antoine Guichet

    Université de Paris, CNRS, Institut Jacques Monod, Paris, France
    Contribution
    Resources, Data curation, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7216-1944
  5. Paul T Conduit

    1. Department of Zoology, University of Cambridge, Cambridge, United Kingdom
    2. Université de Paris, CNRS, Institut Jacques Monod, Paris, France
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    paul.conduit@ijm.fr
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7822-1191

Funding

Wellcome (105653/Z/14/Z)

  • Amrita Mukherjee
  • Paul S Brooks
  • Paul T Conduit

Isaac Newton Trust (18.23(p))

  • Amrita Mukherjee
  • Paul T Conduit

Association pour la Recherche sur le Cancer (PJA 20181208148)

  • Fred Bernard
  • Antoine Guichet

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by a Wellcome Trust and Royal Society Sir Henry Dale Fellowship (105653/Z/14/Z) and an Isaac Newton Trust Research grant (18.23(p)) awarded to PTC, and an Association pour la Recherche sur le Cancer grant (PJA 20181208148) awarded to AG. We thank Sam Comb for help with cloning for the endogenously-tagged fly lines. We thank other members of the Conduit lab for their invaluable input and critical reading of the manuscript. We thank Matthias Landgraf, Melissa Rolls, Adrian Moore, Jill Willdonger for fruitful discussion during the course of the project. We thank Sean Munro and Alison Gillingham for advice on the Golgi and providing us with the Arl1 antibody. We thank Jordan Raff for supplying various antibodies. We thank Darren Williams, Guy Tear, Bing Ye and Yuh-Nung Jan for fly lines that were used in this study. The work benefited from use of the Imaging Facility, Department of Zoology, supported by Matt Wayland and a Sir Isaac Newton Trust Research Grant (18.07ii(c)).

Senior Editor

  1. K VijayRaghavan, National Centre for Biological Sciences, Tata Institute of Fundamental Research, India

Reviewing Editor

  1. Yukiko M Yamashita, University of Michigan, United States

Publication history

  1. Received: May 15, 2020
  2. Accepted: July 12, 2020
  3. Accepted Manuscript published: July 13, 2020 (version 1)
  4. Version of Record published: July 31, 2020 (version 2)
  5. Version of Record updated: August 3, 2020 (version 3)

Copyright

© 2020, Mukherjee et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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